Вакансии

Location: Germany (Remote) Grafana Labs is the company behind Grafana Cloud, the fully managed observability platform trusted by more than 10,000 organizations to ensure reliability, resolve incidents faster, and optimize telemetry at scale. Built on open source and open standards and designed for interoperability across any stack, Grafana Cloud brings AI to observability and observability to AI, giving teams (and their agents) unified visibility so they can see, understand, and act on all their disparate data, wherever it lives, and move at the speed of their ambitions. Customers, including Anthropic, Bloomberg, NVIDIA, Microsoft, and Salesforce, rely on Grafana Labs. We are a 100% remote company with team members across 40+ countries, backed by leading investors including Lightspeed Venture Partners, Sequoia Capital, GIC, Coatue, J.P. Morgan, CapitalG, and Lead Edge Capital. Learn more at grafana.com and follow us on LinkedIn and X . We’re scaling fast and staying true to what makes us different: an open-source legacy, a global collaborative culture, and a passion for meaningful work. Our team thrives in an innovation-driven environment where transparency, autonomy, and trust fuel everything we do. You may not meet every requirement, and that’s okay. If this role excites you, we’d love you to raise your hand for what could be a truly career-defining opportunity. This is a remote opportunity and we would be interested in applications from the UK, Ireland, Sweden, Spain and Germany. The opportunity: Grafana Labs is building a native experimentation platform: a Grafana app that lets teams define A/B tests, connect them to feature flags and product telemetry, and get trustworthy, statistically sound answers about what their changes actually did. It started as a hackathon project and is now used by Grafana engineering and product teams in our internal environment to run real experiments. The next step is to make it a first-class product: one we rely on every day internally and, over time, one we offer to Grafana Cloud customers alongside Frontend Observability, Session Replay and our other user-experience capabilities. You'll join the Product Analytics team , a group of highly technical product analysts who help teams across Grafana understand how our products are used and run experiments on them. As the team's dedicated software engineer, you'll own the engineering of the experimentation app and have a lot of influence over where it goes. You'll partner closely with data scientists on the statistics, data engineers on event pipelines and the data warehouse, software engineers across Grafana on feature flags, Frontend Observability and the App Platform, and product stakeholders who rely on experiment results to make decisions. This is a hands-on engineering role that ships production code. It is not an analyst role. About the product: The experimentation app is built on the Grafana App Platform: Frontend: a TypeScript and React app plugin using @grafana/ui, plus a custom datasource plugin that powers experiment statistics panels. Backend: Go, built with the Grafana App SDK. Experiments are Kubernetes-style custom resources defined in CUE, with an operator, admission webhooks, and support for declarative, GitOps-style management. Feature flags: integration with OpenFeature and the OpenFeature Remote Evaluation Protocol (OFREP) , Grafana's multi-tenant feature toggle service, and an embedded GO Feature Flag evaluator. Statistics engine: a Bayesian analysis engine (TypeScript, with a Go port) that produces a direction-aware verdict per metric, probability to be best, credible intervals, expected loss and sample-size recommendations. Data: experiment exposure and outcome events flow from product instrumentation through RudderStack into BigQuery, or from Grafana Faro into Loki, and are queried live through Grafana datasources. AI: experiment authoring assisted by Grafana Assistant , which discovers relevant data and drafts the experiment configuration for a human to review. What You’ll be doing: Evolve the experimentation app from internal tool to product. Full ownership of features end to end across the React frontend and Go backend, from problem framing and design through rollout, measurement and iteration. Build the experimentation experience. Develop intuitive workflows for defining hypotheses, configuring experiments and metrics, managing their lifecycle, and exploring results. Make these experiences useful for product managers and analysts as well as engineers. Make instrumentation easier to adopt and trust . Evolve the experimentation SDK and its OpenFeature and Faro integrations. Help teams connect variant assignment, actual exposure, and outcome events with consistent identity and event contracts. Connect experiments to the rest of Grafana’s user-experience stack. Integrate with Grafana Faro and Frontend Observability so flag exposures and outcomes are captured automatically, and link experiment results to Session Replay and critical user journeys so teams can see why a variant won, not only that it won. Harden the statistics and analysis path. Work with our data analysts to extend the statistics engine, and make analysis scalable, cost-aware and correct. Examples include moving computation server-side, scheduled analysis, alerting on experiment health, and guardrails against misleading results. Use AI where it genuinely helps. Extend the Grafana Assistant integration for authoring, explaining and reporting on experiments. Raise the engineering bar. Mentor teammates, including analysts who contribute code, through code review, pairing and design docs. Write the architecture decision records (ADRs), docs and demos that help other teams adopt experimentation. Own what you ship. Take part in on-call for the services you build, and support the internal teams that run experiments on them. We invest heavily in developer productivity. You can use modern AI coding assistants as part of your daily workflow (your choice of tools, within security guidelines), backed by a company-funded usage budget so you can iterate quickly without unnecessary friction. We encourage pragmatic AI-assisted development: faster prototyping, test generation, refactors, documentation, and incident follow-ups, always with strong code review and quality standards. You’ll also have access to the latest frontier models from OpenAI, Anthropic, and Google. What makes you a great fit: We highly value people who are intellectually curious, default to transparency, have a strong bias towards action, and are kind and enjoy working as a team. Strong full-stack engineering experience. You’ve built and operated production web applications with TypeScript and React, and backend services in Go (or a similar language, with willingness to work in Go). You value maintainability, automated testing and secure development practices. Experience building an in-house platform or integrating existing experimentation and A/B testing platform (for example Statsig, Eppo, GrowthBook, Optimizely, LaunchDarkly experiments, or an in-house platform). Product and data intuition. You care whether what you shipped actually moved the needle, and you’re comfortable working with event data, SQL and data warehouses such as BigQuery. Technical ownership. You’ve delivered complex projects with minimal supervision, broken them into short feedback loops (analyze, design, ship an MVP, learn, iterate), and helped teammates work more effectively. Operational responsibility. You’ve been on call, supported software in production, and know how to make systems observable and debuggable. Pragmatic AI usage. You use AI coding tools thoughtfully, validate their output, and share practices that improve the team’s speed and quality. Clear communication. You can explain technical and statistical tradeoffs to engineers, analysts and product managers in a fully remote, asynchronous environment. Bonus Points For: Hands-on experience with feature flags and OpenFeature. A working understanding of experiment statistics: Bayesian or frequentist testing, sample sizing, variance reduction, and common pitfalls such as peeking and sample ratio mismatch. Experience with Kubernetes concepts: custom resources, operators, admission webhooks, GitOps. Experience building Grafana plugins or apps, or with the Grafana App SDK or Scenes. Familiarity with frontend observability and product analytics tooling, such as Grafana Faro, RUM, session replay, RudderStack or Segment. Open source contribution or maintainership. Experience as a user of Grafana, Prometheus, Loki or Tempo, whether at work or on a homelab. Compensation & Rewards: In Germany, the base compensation range for this role is € 100,000 - €125,000 . Actual compensation may vary based on level, experience, and skillset as assessed throughout the interview process. All of our roles include Restricted Stock Units (RSUs), giving every team member ownership in Grafana Labs' success. We believe in shared outcomes—RSUs help us stay aligned and invested as we scale globally. *Compensation ranges are country specific. If you are applying for this role from a different location than listed above, your recruiter will discuss your specific market’s defined pay range & benefits at the beginning of the process. Why You’ll Thrive at Grafana Labs: 100% Remote, Global Culture - As a remote-only company, we bring together talent from around the world, united by a culture of collaboration and shared purpose. Scaling Organization – Tackle meaningful work in a high-growth, ever-evolving environment. Transparent Communication – Expect open decision-making and regular company-wide updates. Innovation-Driven – Autonomy and support to ship great work and try new things. Open Source Roots – Built on community-driven values that shape how we work. Empowered Teams – High trust, low ego culture that values outcomes over optics. Career Growth Pathways – Defined opportunities to grow and develop your career. Approachable Leadership – Transparent execs who are involved, visible, and human. Passionate People – Join a team of smart, supportive folks who care deeply about what they do. In-Person onboarding - We want you to thrive from day 1 with your fellow new ‘Grafanistas’ to learn all about what we do and how we do it. Balance is Key - We operate a global annual leave policy of 30 days per annum. 3 days of your annual leave entitlement are reserved for Grafana Shutdown Days to allow the team to really disconnect. *We will comply with local legislation where applicable. Equal Opportunity Employer: Grafana Labs is an equal opportunities employer. We welcome applications from everyone regardless of race, colour, nationality, origin, caste, sex, gender reassignment identity or expression, sexual orientation, age, religion or belief, disability, veteran status, genetic information, pregnancy, maternity, marital, family or carer status, or any other characteristic which is protected by local law. We believe that equality and diversity build a strong organisation, and we work hard to ensure that is the foundation of our organisation as we grow. Grafana Labs may utilize AI tools in its recruitment process to assist in matching information provided in CVs to job postings. The recruitment team will continue to review inbound CVs manually to identify alignment with current openings. #LI-Remote For information about how your personal data is used once you’ve applied to a job, check out our privacy policy .

Location: Spain (Remote) Grafana Labs is the company behind Grafana Cloud, the fully managed observability platform trusted by more than 10,000 organizations to ensure reliability, resolve incidents faster, and optimize telemetry at scale. Built on open source and open standards and designed for interoperability across any stack, Grafana Cloud brings AI to observability and observability to AI, giving teams (and their agents) unified visibility so they can see, understand, and act on all their disparate data, wherever it lives, and move at the speed of their ambitions. Customers, including Anthropic, Bloomberg, NVIDIA, Microsoft, and Salesforce, rely on Grafana Labs. We are a 100% remote company with team members across 40+ countries, backed by leading investors including Lightspeed Venture Partners, Sequoia Capital, GIC, Coatue, J.P. Morgan, CapitalG, and Lead Edge Capital. Learn more at grafana.com and follow us on LinkedIn and X . We’re scaling fast and staying true to what makes us different: an open-source legacy, a global collaborative culture, and a passion for meaningful work. Our team thrives in an innovation-driven environment where transparency, autonomy, and trust fuel everything we do. You may not meet every requirement, and that’s okay. If this role excites you, we’d love you to raise your hand for what could be a truly career-defining opportunity. This is a remote opportunity and we would be interested in applications from the UK, Ireland, Sweden, Spain and Germany. The opportunity: Grafana Labs is building a native experimentation platform: a Grafana app that lets teams define A/B tests, connect them to feature flags and product telemetry, and get trustworthy, statistically sound answers about what their changes actually did. It started as a hackathon project and is now used by Grafana engineering and product teams in our internal environment to run real experiments. The next step is to make it a first-class product: one we rely on every day internally and, over time, one we offer to Grafana Cloud customers alongside Frontend Observability, Session Replay and our other user-experience capabilities. You'll join the Product Analytics team , a group of highly technical product analysts who help teams across Grafana understand how our products are used and run experiments on them. As the team's dedicated software engineer, you'll own the engineering of the experimentation app and have a lot of influence over where it goes. You'll partner closely with data scientists on the statistics, data engineers on event pipelines and the data warehouse, software engineers across Grafana on feature flags, Frontend Observability and the App Platform, and product stakeholders who rely on experiment results to make decisions. This is a hands-on engineering role that ships production code. It is not an analyst role. About the product: The experimentation app is built on the Grafana App Platform: Frontend: a TypeScript and React app plugin using @grafana/ui, plus a custom datasource plugin that powers experiment statistics panels. Backend: Go, built with the Grafana App SDK. Experiments are Kubernetes-style custom resources defined in CUE, with an operator, admission webhooks, and support for declarative, GitOps-style management. Feature flags: integration with OpenFeature and the OpenFeature Remote Evaluation Protocol (OFREP) , Grafana's multi-tenant feature toggle service, and an embedded GO Feature Flag evaluator. Statistics engine: a Bayesian analysis engine (TypeScript, with a Go port) that produces a direction-aware verdict per metric, probability to be best, credible intervals, expected loss and sample-size recommendations. Data: experiment exposure and outcome events flow from product instrumentation through RudderStack into BigQuery, or from Grafana Faro into Loki, and are queried live through Grafana datasources. AI: experiment authoring assisted by Grafana Assistant , which discovers relevant data and drafts the experiment configuration for a human to review. What You’ll be doing: Evolve the experimentation app from internal tool to product. Full ownership of features end to end across the React frontend and Go backend, from problem framing and design through rollout, measurement and iteration. Build the experimentation experience. Develop intuitive workflows for defining hypotheses, configuring experiments and metrics, managing their lifecycle, and exploring results. Make these experiences useful for product managers and analysts as well as engineers. Make instrumentation easier to adopt and trust . Evolve the experimentation SDK and its OpenFeature and Faro integrations. Help teams connect variant assignment, actual exposure, and outcome events with consistent identity and event contracts. Connect experiments to the rest of Grafana’s user-experience stack. Integrate with Grafana Faro and Frontend Observability so flag exposures and outcomes are captured automatically, and link experiment results to Session Replay and critical user journeys so teams can see why a variant won, not only that it won. Harden the statistics and analysis path. Work with our data analysts to extend the statistics engine, and make analysis scalable, cost-aware and correct. Examples include moving computation server-side, scheduled analysis, alerting on experiment health, and guardrails against misleading results. Use AI where it genuinely helps. Extend the Grafana Assistant integration for authoring, explaining and reporting on experiments. Raise the engineering bar. Mentor teammates, including analysts who contribute code, through code review, pairing and design docs. Write the architecture decision records (ADRs), docs and demos that help other teams adopt experimentation. Own what you ship. Take part in on-call for the services you build, and support the internal teams that run experiments on them. We invest heavily in developer productivity. You can use modern AI coding assistants as part of your daily workflow (your choice of tools, within security guidelines), backed by a company-funded usage budget so you can iterate quickly without unnecessary friction. We encourage pragmatic AI-assisted development: faster prototyping, test generation, refactors, documentation, and incident follow-ups, always with strong code review and quality standards. You’ll also have access to the latest frontier models from OpenAI, Anthropic, and Google. What makes you a great fit: We highly value people who are intellectually curious, default to transparency, have a strong bias towards action, and are kind and enjoy working as a team. Strong full-stack engineering experience. You’ve built and operated production web applications with TypeScript and React, and backend services in Go (or a similar language, with willingness to work in Go). You value maintainability, automated testing and secure development practices. Experience building an in-house platform or integrating existing experimentation and A/B testing platform (for example Statsig, Eppo, GrowthBook, Optimizely, LaunchDarkly experiments, or an in-house platform). Product and data intuition. You care whether what you shipped actually moved the needle, and you’re comfortable working with event data, SQL and data warehouses such as BigQuery. Technical ownership. You’ve delivered complex projects with minimal supervision, broken them into short feedback loops (analyze, design, ship an MVP, learn, iterate), and helped teammates work more effectively. Operational responsibility. You’ve been on call, supported software in production, and know how to make systems observable and debuggable. Pragmatic AI usage. You use AI coding tools thoughtfully, validate their output, and share practices that improve the team’s speed and quality. Clear communication. You can explain technical and statistical tradeoffs to engineers, analysts and product managers in a fully remote, asynchronous environment. Bonus Points For: Hands-on experience with feature flags and OpenFeature. A working understanding of experiment statistics: Bayesian or frequentist testing, sample sizing, variance reduction, and common pitfalls such as peeking and sample ratio mismatch. Experience with Kubernetes concepts: custom resources, operators, admission webhooks, GitOps. Experience building Grafana plugins or apps, or with the Grafana App SDK or Scenes. Familiarity with frontend observability and product analytics tooling, such as Grafana Faro, RUM, session replay, RudderStack or Segment. Open source contribution or maintainership. Experience as a user of Grafana, Prometheus, Loki or Tempo, whether at work or on a homelab. Compensation & Rewards: In Spain, the base compensation range for this role is €85 ,000 - €107,000 . Actual compensation may vary based on level, experience, and skillset as assessed throughout the interview process. All of our roles include Restricted Stock Units (RSUs), giving every team member ownership in Grafana Labs' success. We believe in shared outcomes—RSUs help us stay aligned and invested as we scale globally. *Compensation ranges are country specific. If you are applying for this role from a different location than listed above, your recruiter will discuss your specific market’s defined pay range & benefits at the beginning of the process. Why You’ll Thrive at Grafana Labs: 100% Remote, Global Culture - As a remote-only company, we bring together talent from around the world, united by a culture of collaboration and shared purpose. Scaling Organization – Tackle meaningful work in a high-growth, ever-evolving environment. Transparent Communication – Expect open decision-making and regular company-wide updates. Innovation-Driven – Autonomy and support to ship great work and try new things. Open Source Roots – Built on community-driven values that shape how we work. Empowered Teams – High trust, low ego culture that values outcomes over optics. Career Growth Pathways – Defined opportunities to grow and develop your career. Approachable Leadership – Transparent execs who are involved, visible, and human. Passionate People – Join a team of smart, supportive folks who care deeply about what they do. In-Person onboarding - We want you to thrive from day 1 with your fellow new ‘Grafanistas’ to learn all about what we do and how we do it. Balance is Key - We operate a global annual leave policy of 30 days per annum. 3 days of your annual leave entitlement are reserved for Grafana Shutdown Days to allow the team to really disconnect. *We will comply with local legislation where applicable. Equal Opportunity Employer: Grafana Labs is an equal opportunities employer. We welcome applications from everyone regardless of race, colour, nationality, origin, caste, sex, gender reassignment identity or expression, sexual orientation, age, religion or belief, disability, veteran status, genetic information, pregnancy, maternity, marital, family or carer status, or any other characteristic which is protected by local law. We believe that equality and diversity build a strong organisation, and we work hard to ensure that is the foundation of our organisation as we grow. Grafana Labs may utilize AI tools in its recruitment process to assist in matching information provided in CVs to job postings. The recruitment team will continue to review inbound CVs manually to identify alignment with current openings. #LI-Remote For information about how your personal data is used once you’ve applied to a job, check out our privacy policy .

Location: Republic of Ireland (Remote) Grafana Labs is the company behind Grafana Cloud, the fully managed observability platform trusted by more than 10,000 organizations to ensure reliability, resolve incidents faster, and optimize telemetry at scale. Built on open source and open standards and designed for interoperability across any stack, Grafana Cloud brings AI to observability and observability to AI, giving teams (and their agents) unified visibility so they can see, understand, and act on all their disparate data, wherever it lives, and move at the speed of their ambitions. Customers, including Anthropic, Bloomberg, NVIDIA, Microsoft, and Salesforce, rely on Grafana Labs. We are a 100% remote company with team members across 40+ countries, backed by leading investors including Lightspeed Venture Partners, Sequoia Capital, GIC, Coatue, J.P. Morgan, CapitalG, and Lead Edge Capital. Learn more at grafana.com and follow us on LinkedIn and X . We’re scaling fast and staying true to what makes us different: an open-source legacy, a global collaborative culture, and a passion for meaningful work. Our team thrives in an innovation-driven environment where transparency, autonomy, and trust fuel everything we do. You may not meet every requirement, and that’s okay. If this role excites you, we’d love you to raise your hand for what could be a truly career-defining opportunity. This is a remote opportunity and we would be interested in applications from the UK, Ireland, Sweden, Spain and Germany. The opportunity: Grafana Labs is building a native experimentation platform: a Grafana app that lets teams define A/B tests, connect them to feature flags and product telemetry, and get trustworthy, statistically sound answers about what their changes actually did. It started as a hackathon project and is now used by Grafana engineering and product teams in our internal environment to run real experiments. The next step is to make it a first-class product: one we rely on every day internally and, over time, one we offer to Grafana Cloud customers alongside Frontend Observability, Session Replay and our other user-experience capabilities. You'll join the Product Analytics team , a group of highly technical product analysts who help teams across Grafana understand how our products are used and run experiments on them. As the team's dedicated software engineer, you'll own the engineering of the experimentation app and have a lot of influence over where it goes. You'll partner closely with data scientists on the statistics, data engineers on event pipelines and the data warehouse, software engineers across Grafana on feature flags, Frontend Observability and the App Platform, and product stakeholders who rely on experiment results to make decisions. This is a hands-on engineering role that ships production code. It is not an analyst role. About the product: The experimentation app is built on the Grafana App Platform: Frontend: a TypeScript and React app plugin using @grafana/ui, plus a custom datasource plugin that powers experiment statistics panels. Backend: Go, built with the Grafana App SDK. Experiments are Kubernetes-style custom resources defined in CUE, with an operator, admission webhooks, and support for declarative, GitOps-style management. Feature flags: integration with OpenFeature and the OpenFeature Remote Evaluation Protocol (OFREP) , Grafana's multi-tenant feature toggle service, and an embedded GO Feature Flag evaluator. Statistics engine: a Bayesian analysis engine (TypeScript, with a Go port) that produces a direction-aware verdict per metric, probability to be best, credible intervals, expected loss and sample-size recommendations. Data: experiment exposure and outcome events flow from product instrumentation through RudderStack into BigQuery, or from Grafana Faro into Loki, and are queried live through Grafana datasources. AI: experiment authoring assisted by Grafana Assistant , which discovers relevant data and drafts the experiment configuration for a human to review. What You’ll be doing: Evolve the experimentation app from internal tool to product. Full ownership of features end to end across the React frontend and Go backend, from problem framing and design through rollout, measurement and iteration. Build the experimentation experience. Develop intuitive workflows for defining hypotheses, configuring experiments and metrics, managing their lifecycle, and exploring results. Make these experiences useful for product managers and analysts as well as engineers. Make instrumentation easier to adopt and trust . Evolve the experimentation SDK and its OpenFeature and Faro integrations. Help teams connect variant assignment, actual exposure, and outcome events with consistent identity and event contracts. Connect experiments to the rest of Grafana’s user-experience stack. Integrate with Grafana Faro and Frontend Observability so flag exposures and outcomes are captured automatically, and link experiment results to Session Replay and critical user journeys so teams can see why a variant won, not only that it won. Harden the statistics and analysis path. Work with our data analysts to extend the statistics engine, and make analysis scalable, cost-aware and correct. Examples include moving computation server-side, scheduled analysis, alerting on experiment health, and guardrails against misleading results. Use AI where it genuinely helps. Extend the Grafana Assistant integration for authoring, explaining and reporting on experiments. Raise the engineering bar. Mentor teammates, including analysts who contribute code, through code review, pairing and design docs. Write the architecture decision records (ADRs), docs and demos that help other teams adopt experimentation. Own what you ship. Take part in on-call for the services you build, and support the internal teams that run experiments on them. We invest heavily in developer productivity. You can use modern AI coding assistants as part of your daily workflow (your choice of tools, within security guidelines), backed by a company-funded usage budget so you can iterate quickly without unnecessary friction. We encourage pragmatic AI-assisted development: faster prototyping, test generation, refactors, documentation, and incident follow-ups, always with strong code review and quality standards. You’ll also have access to the latest frontier models from OpenAI, Anthropic, and Google. What makes you a great fit: We highly value people who are intellectually curious, default to transparency, have a strong bias towards action, and are kind and enjoy working as a team. Strong full-stack engineering experience. You’ve built and operated production web applications with TypeScript and React, and backend services in Go (or a similar language, with willingness to work in Go). You value maintainability, automated testing and secure development practices. Experience building an in-house platform or integrating existing experimentation and A/B testing platform (for example Statsig, Eppo, GrowthBook, Optimizely, LaunchDarkly experiments, or an in-house platform). Product and data intuition. You care whether what you shipped actually moved the needle, and you’re comfortable working with event data, SQL and data warehouses such as BigQuery. Technical ownership. You’ve delivered complex projects with minimal supervision, broken them into short feedback loops (analyze, design, ship an MVP, learn, iterate), and helped teammates work more effectively. Operational responsibility. You’ve been on call, supported software in production, and know how to make systems observable and debuggable. Pragmatic AI usage. You use AI coding tools thoughtfully, validate their output, and share practices that improve the team’s speed and quality. Clear communication. You can explain technical and statistical tradeoffs to engineers, analysts and product managers in a fully remote, asynchronous environment. Bonus Points For: Hands-on experience with feature flags and OpenFeature. A working understanding of experiment statistics: Bayesian or frequentist testing, sample sizing, variance reduction, and common pitfalls such as peeking and sample ratio mismatch. Experience with Kubernetes concepts: custom resources, operators, admission webhooks, GitOps. Experience building Grafana plugins or apps, or with the Grafana App SDK or Scenes. Familiarity with frontend observability and product analytics tooling, such as Grafana Faro, RUM, session replay, RudderStack or Segment. Open source contribution or maintainership. Experience as a user of Grafana, Prometheus, Loki or Tempo, whether at work or on a homelab. Compensation & Rewards: In Ireland, the base compensation range for this role is EUR 107,000 - EUR 134,000 . Actual compensation may vary based on level, experience, and skillset as assessed throughout the interview process. All of our roles include Restricted Stock Units (RSUs), giving every team member ownership in Grafana Labs' success. We believe in shared outcomes—RSUs help us stay aligned and invested as we scale globally. *Compensation ranges are country specific. If you are applying for this role from a different location than listed above, your recruiter will discuss your specific market’s defined pay range & benefits at the beginning of the process. Why You’ll Thrive at Grafana Labs: 100% Remote, Global Culture - As a remote-only company, we bring together talent from around the world, united by a culture of collaboration and shared purpose. Scaling Organization – Tackle meaningful work in a high-growth, ever-evolving environment. Transparent Communication – Expect open decision-making and regular company-wide updates. Innovation-Driven – Autonomy and support to ship great work and try new things. Open Source Roots – Built on community-driven values that shape how we work. Empowered Teams – High trust, low ego culture that values outcomes over optics. Career Growth Pathways – Defined opportunities to grow and develop your career. Approachable Leadership – Transparent execs who are involved, visible, and human. Passionate People – Join a team of smart, supportive folks who care deeply about what they do. In-Person onboarding - We want you to thrive from day 1 with your fellow new ‘Grafanistas’ to learn all about what we do and how we do it. Balance is Key - We operate a global annual leave policy of 30 days per annum. 3 days of your annual leave entitlement are reserved for Grafana Shutdown Days to allow the team to really disconnect. *We will comply with local legislation where applicable. Equal Opportunity Employer: Grafana Labs is an equal opportunities employer. We welcome applications from everyone regardless of race, colour, nationality, origin, caste, sex, gender reassignment identity or expression, sexual orientation, age, religion or belief, disability, veteran status, genetic information, pregnancy, maternity, marital, family or carer status, or any other characteristic which is protected by local law. We believe that equality and diversity build a strong organisation, and we work hard to ensure that is the foundation of our organisation as we grow. Grafana Labs may utilize AI tools in its recruitment process to assist in matching information provided in CVs to job postings. The recruitment team will continue to review inbound CVs manually to identify alignment with current openings. #LI-Remote For information about how your personal data is used once you’ve applied to a job, check out our privacy policy .

Location: United Kingdom (Remote) Grafana Labs is the company behind Grafana Cloud, the fully managed observability platform trusted by more than 10,000 organizations to ensure reliability, resolve incidents faster, and optimize telemetry at scale. Built on open source and open standards and designed for interoperability across any stack, Grafana Cloud brings AI to observability and observability to AI, giving teams (and their agents) unified visibility so they can see, understand, and act on all their disparate data, wherever it lives, and move at the speed of their ambitions. Customers, including Anthropic, Bloomberg, NVIDIA, Microsoft, and Salesforce, rely on Grafana Labs. We are a 100% remote company with team members across 40+ countries, backed by leading investors including Lightspeed Venture Partners, Sequoia Capital, GIC, Coatue, J.P. Morgan, CapitalG, and Lead Edge Capital. Learn more at grafana.com and follow us on LinkedIn and X . We’re scaling fast and staying true to what makes us different: an open-source legacy, a global collaborative culture, and a passion for meaningful work. Our team thrives in an innovation-driven environment where transparency, autonomy, and trust fuel everything we do. You may not meet every requirement, and that’s okay. If this role excites you, we’d love you to raise your hand for what could be a truly career-defining opportunity. This is a remote opportunity and we would be interested in applications from the UK, Ireland, Sweden, Spain and Germany. The opportunity: Grafana Labs is building a native experimentation platform: a Grafana app that lets teams define A/B tests, connect them to feature flags and product telemetry, and get trustworthy, statistically sound answers about what their changes actually did. It started as a hackathon project and is now used by Grafana engineering and product teams in our internal environment to run real experiments. The next step is to make it a first-class product: one we rely on every day internally and, over time, one we offer to Grafana Cloud customers alongside Frontend Observability, Session Replay and our other user-experience capabilities. You'll join the Product Analytics team , a group of highly technical product analysts who help teams across Grafana understand how our products are used and run experiments on them. As the team's dedicated software engineer, you'll own the engineering of the experimentation app and have a lot of influence over where it goes. You'll partner closely with data scientists on the statistics, data engineers on event pipelines and the data warehouse, software engineers across Grafana on feature flags, Frontend Observability and the App Platform, and product stakeholders who rely on experiment results to make decisions. This is a hands-on engineering role that ships production code. It is not an analyst role. About the product: The experimentation app is built on the Grafana App Platform: Frontend: a TypeScript and React app plugin using @grafana/ui, plus a custom datasource plugin that powers experiment statistics panels. Backend: Go, built with the Grafana App SDK. Experiments are Kubernetes-style custom resources defined in CUE, with an operator, admission webhooks, and support for declarative, GitOps-style management. Feature flags: integration with OpenFeature and the OpenFeature Remote Evaluation Protocol (OFREP) , Grafana's multi-tenant feature toggle service, and an embedded GO Feature Flag evaluator. Statistics engine: a Bayesian analysis engine (TypeScript, with a Go port) that produces a direction-aware verdict per metric, probability to be best, credible intervals, expected loss and sample-size recommendations. Data: experiment exposure and outcome events flow from product instrumentation through RudderStack into BigQuery, or from Grafana Faro into Loki, and are queried live through Grafana datasources. AI: experiment authoring assisted by Grafana Assistant , which discovers relevant data and drafts the experiment configuration for a human to review. What You’ll be doing: Evolve the experimentation app from internal tool to product. Full ownership of features end to end across the React frontend and Go backend, from problem framing and design through rollout, measurement and iteration. Build the experimentation experience. Develop intuitive workflows for defining hypotheses, configuring experiments and metrics, managing their lifecycle, and exploring results. Make these experiences useful for product managers and analysts as well as engineers. Make instrumentation easier to adopt and trust . Evolve the experimentation SDK and its OpenFeature and Faro integrations. Help teams connect variant assignment, actual exposure, and outcome events with consistent identity and event contracts. Connect experiments to the rest of Grafana’s user-experience stack. Integrate with Grafana Faro and Frontend Observability so flag exposures and outcomes are captured automatically, and link experiment results to Session Replay and critical user journeys so teams can see why a variant won, not only that it won. Harden the statistics and analysis path. Work with our data analysts to extend the statistics engine, and make analysis scalable, cost-aware and correct. Examples include moving computation server-side, scheduled analysis, alerting on experiment health, and guardrails against misleading results. Use AI where it genuinely helps. Extend the Grafana Assistant integration for authoring, explaining and reporting on experiments. Raise the engineering bar. Mentor teammates, including analysts who contribute code, through code review, pairing and design docs. Write the architecture decision records (ADRs), docs and demos that help other teams adopt experimentation. Own what you ship. Take part in on-call for the services you build, and support the internal teams that run experiments on them. We invest heavily in developer productivity. You can use modern AI coding assistants as part of your daily workflow (your choice of tools, within security guidelines), backed by a company-funded usage budget so you can iterate quickly without unnecessary friction. We encourage pragmatic AI-assisted development: faster prototyping, test generation, refactors, documentation, and incident follow-ups, always with strong code review and quality standards. You’ll also have access to the latest frontier models from OpenAI, Anthropic, and Google. What makes you a great fit: We highly value people who are intellectually curious, default to transparency, have a strong bias towards action, and are kind and enjoy working as a team. Strong full-stack engineering experience. You’ve built and operated production web applications with TypeScript and React, and backend services in Go (or a similar language, with willingness to work in Go). You value maintainability, automated testing and secure development practices. Experience building an in-house platform or integrating existing experimentation and A/B testing platform (for example Statsig, Eppo, GrowthBook, Optimizely, LaunchDarkly experiments, or an in-house platform). Product and data intuition. You care whether what you shipped actually moved the needle, and you’re comfortable working with event data, SQL and data warehouses such as BigQuery. Technical ownership. You’ve delivered complex projects with minimal supervision, broken them into short feedback loops (analyze, design, ship an MVP, learn, iterate), and helped teammates work more effectively. Operational responsibility. You’ve been on call, supported software in production, and know how to make systems observable and debuggable. Pragmatic AI usage. You use AI coding tools thoughtfully, validate their output, and share practices that improve the team’s speed and quality. Clear communication. You can explain technical and statistical tradeoffs to engineers, analysts and product managers in a fully remote, asynchronous environment. Bonus Points For: Hands-on experience with feature flags and OpenFeature. A working understanding of experiment statistics: Bayesian or frequentist testing, sample sizing, variance reduction, and common pitfalls such as peeking and sample ratio mismatch. Experience with Kubernetes concepts: custom resources, operators, admission webhooks, GitOps. Experience building Grafana plugins or apps, or with the Grafana App SDK or Scenes. Familiarity with frontend observability and product analytics tooling, such as Grafana Faro, RUM, session replay, RudderStack or Segment. Open source contribution or maintainership. Experience as a user of Grafana, Prometheus, Loki or Tempo, whether at work or on a homelab. Compensation & Rewards: In the UK, the base compensation range for this role is £94 ,000 - £118,000 . Actual compensation may vary based on level, experience, and skillset as assessed throughout the interview process. All of our roles include Restricted Stock Units (RSUs), giving every team member ownership in Grafana Labs' success. We believe in shared outcomes—RSUs help us stay aligned and invested as we scale globally. *Compensation ranges are country specific. If you are applying for this role from a different location than listed above, your recruiter will discuss your specific market’s defined pay range & benefits at the beginning of the process. Why You’ll Thrive at Grafana Labs: 100% Remote, Global Culture - As a remote-only company, we bring together talent from around the world, united by a culture of collaboration and shared purpose. Scaling Organization – Tackle meaningful work in a high-growth, ever-evolving environment. Transparent Communication – Expect open decision-making and regular company-wide updates. Innovation-Driven – Autonomy and support to ship great work and try new things. Open Source Roots – Built on community-driven values that shape how we work. Empowered Teams – High trust, low ego culture that values outcomes over optics. Career Growth Pathways – Defined opportunities to grow and develop your career. Approachable Leadership – Transparent execs who are involved, visible, and human. Passionate People – Join a team of smart, supportive folks who care deeply about what they do. In-Person onboarding - We want you to thrive from day 1 with your fellow new ‘Grafanistas’ to learn all about what we do and how we do it. Balance is Key - We operate a global annual leave policy of 30 days per annum. 3 days of your annual leave entitlement are reserved for Grafana Shutdown Days to allow the team to really disconnect. *We will comply with local legislation where applicable. Equal Opportunity Employer: Grafana Labs is an equal opportunities employer. We welcome applications from everyone regardless of race, colour, nationality, origin, caste, sex, gender reassignment identity or expression, sexual orientation, age, religion or belief, disability, veteran status, genetic information, pregnancy, maternity, marital, family or carer status, or any other characteristic which is protected by local law. We believe that equality and diversity build a strong organisation, and we work hard to ensure that is the foundation of our organisation as we grow. Grafana Labs may utilize AI tools in its recruitment process to assist in matching information provided in CVs to job postings. The recruitment team will continue to review inbound CVs manually to identify alignment with current openings. #LI-Remote For information about how your personal data is used once you’ve applied to a job, check out our privacy policy .

Location: San Juan, Puerto Rico; New York, NY; District of Columbia; Europe | Spain Workplace: Hybrid About the Company Rain is the global stablecoin payments platform for enterprises, neobanks, platforms, developers, and AI agents. Our technology allows partners to move, store, and use stablecoins instantly and compliantly through global payment cards, rewards, on/offramps, wallets, and cross-border rails. As both a Visa and Mastercard Principal Member, Rain issues cards that work at more than 175 million merchant locations in over 220 countries and territories. Built natively for stablecoins and trusted by more than 100 organizations worldwide, Rain delivers secure, scalable infrastructure that makes money move freely and instantly around the world. You will have the opportunity to deliver massive impact at a hypergrowth company backed by some of the top investors in fintech, crypto, and SaaS. In January 2026, we closed a $250M Series C led by ICONIQ, valuing Rain at $1.95B, with Sapphire Ventures, Norwest, Galaxy Ventures, Dragonfly, Bessemer Venture Partners, FirstMark, Lightspeed, and Endeavor Catalyst also participating. If you're curious, bold, and excited to help shape a borderless financial future, we'd love to talk. Our Ethos We believe in an open and flat structure. You will be able to grow into the role that most aligns with your goals. Our team members at all levels have the freedom to explore ideas and impact the roadmap and vision of our company. About the role Rain builds payments and stablecoin infrastructure. Finance, Risk, Compliance, and our partners rely on data from card transactions, settlements, ledger entries, and onchain transfers. We’re looking for a Data Engineer with batch and streaming experience to bring this data into our warehouse and keep it correct. You’ll build scalable, idempotent pipelines that handle late and duplicate data and alert us when something breaks. At Rain, everyone models data, writes production-quality code, and automates their own workflows. We use AI to speed up repetitive work, but we own and check the results. In this role, you’ll automate ingestion and quality checks so new sources come online quickly and stay trustworthy. What you’ll do - Build scalable batch and streaming pipelines, choosing the right approach for latency, cost, and correctness. - Process events near real time, handling deduplication, windowing, and late or out-of-order events. - Own batch ingestion from databases (CDC), files (SFTP and GCS), APIs, and onchain sources. - Build incremental dbt models that handle late data, duplicates, CDC deletes, and backfills; reconcile streaming and batch outputs. - Orchestrate pipelines in Dagster with sensors, schedules, and alerts. - Add freshness, volume, and reconciliation checks to every source, and fix root causes. - Work with backend pods on event and table contracts to prevent downstream breakage. - Partner with Analytics Engineers, Data Scientists, and Risk on their data needs, including ML features. What you’ll need - At least 3 years building production data solutions, including owning both batch and streaming pipelines end to end, from source to warehouse. - Experience designing data solutions at scale. - Strong SQL and Python / Rust, plus experience with a cloud data warehouse such as BigQuery, ClickHouse, or Snowflake and an understanding of their trade-offs. - Streaming experience with tools such as Pub/Sub, Kafka, Dataflow/Beam, or Flink. - Batch experience with dbt and an orchestrator such as Dagster or Airflow. - Experience with production data quality testing, monitoring, and reconciliation. - Ability to debug across the source database, pipeline, warehouse, and report. - Ability to use AI tools to learn and work faster while checking their output. Nice to have - Building offline and real-time ML feature pipelines, such as fraud or risk features. - Working with payments, banking, or blockchain data, including EVM or Solana events and indexers. - Using CDC and ingestion tools such as Datastream, Debezium, Meltano, Fivetran, or Airbyte. - Experience with GCP. Things that enable a fulfilling, healthy and happy experience at Rain: Flexible time off 🌴 Unlimited vacation can be daunting, so we require Rainmakers to take 10 days minimum for themselves. Flexible working ☕ We support a flexible workplace – work from home, come into an office, or both. We want everyone to work in an environment where they're their most confident and productive selves. New Rainmakers receive a stipend to set up a comfortable home workspace. Easy to access benefits 🧠 For US Rainmakers, we cover 95% of your health, dental, and vision plan costs and 90% for your dependents, plus a 100% company-subsidized life insurance plan. Retirement goals💡 Plan for the future with confidence. We offer a 401(k) with a 4% company match. Equity plan 📦 Every Rainmaker gets an equity option plan so we all benefit from our success. Health and Wellness 📚 High performance begins from within. Rainmakers receive a monthly stipend to be used for eligible health and wellness spending like gym memberships/fitness classes, massages, acupuncture - whatever recharges you! In-office meals 🍜 Rainmakers working from the office enjoy lunch and dinner on us, covered with a DoorDash credit. Team summits ✨ Summits play an important role at Rain. Time together helps us build relationships and a common destiny. Expect team and company offsites, both domestic and international.

Location: San Juan, Puerto Rico; New York, NY; District of Columbia; Europe | Spain Workplace: OnSite About the Company Rain is the global stablecoin payments platform for enterprises, neobanks, platforms, developers, and AI agents. Our technology allows partners to move, store, and use stablecoins instantly and compliantly through global payment cards, rewards, on/offramps, wallets, and cross-border rails. As both a Visa and Mastercard Principal Member, Rain issues cards that work at more than 175 million merchant locations in over 220 countries and territories. Built natively for stablecoins and trusted by more than 100 organizations worldwide, Rain delivers secure, scalable infrastructure that makes money move freely and instantly around the world. You will have the opportunity to deliver massive impact at a hypergrowth company backed by some of the top investors in fintech, crypto, and SaaS. In January 2026, we closed a $250M Series C led by ICONIQ, valuing Rain at $1.95B, with Sapphire Ventures, Norwest, Galaxy Ventures, Dragonfly, Bessemer Venture Partners, FirstMark, Lightspeed, and Endeavor Catalyst also participating. If you're curious, bold, and excited to help shape a borderless financial future, we'd love to talk. Our Ethos We believe in an open and flat structure. You will be able to grow into the role that most aligns with your goals. Our team members at all levels have the freedom to explore ideas and impact the roadmap and vision of our company. About the role Rain is building payments and stablecoin infrastructure, and our data platform holds some of the most sensitive data a company can have: cardholder, ledger, and partner data across many countries. We’re looking for a Data Platform Engineer who has built and run data platforms for both batch and streaming to own the platform our data team and engineering pods depend on: the warehouse, streaming infrastructure, orchestration, BI, ML platform, access controls, and the tooling that makes all of it safe, reliable, and cost-efficient. Your product is the platform, and your customers are the engineers, analysts, and scientists who build on it. You’ll own the platform layer: the data and ML platform, the infrastructure for ingestion and processing in batch and streaming, data governance and security compliance, the warehouse, and the analytics and BI tooling. Data Engineers, Analytics Engineers, Data Scientists, and engineering pods build on it to run experiments, operate reliably, and turn data into decisions. At Rain, we’re builders who use AI to automate repetitive work. That changes what data roles look like: where a data scientist used to only analyze and an analyst used to only build dashboards, here everyone models data, writes production-quality code, and automates their own workflows. You own the result, including checking what the AI produces. For this role, that means automating access, deploys, and governance so the platform runs itself and stays compliant. What you’ll do - Design and build data platforms at scale for both batch and streaming, choosing storage, compute, and processing based on latency, cost, and reliability needs. - Own the infrastructure for BigQuery, streaming (such as Pub/Sub or Kafka, and Dataflow or Flink), Dagster+, and Lightdash as code, including environments, CI/CD, and deploys. - Own access and governance: IAM, policy tags, PII contracts, masked and no-PII access paths, and audit logs, across tables and streams. - Provide ML platform capabilities: feature pipelines, training data, and serving real-time features to fraud and risk models. - Build platform tooling: templates, CI checks, schema registry and data contracts, catalog, and lineage. - Monitor platform reliability, latency, and cost, and fix what is slow or expensive. - Design how backend events and CDC land in the warehouse, and advise backend pods on event design. - Respond to platform incidents and access requests, and automate the repetitive ones away. What you’ll need - At least 4 years building and running data platforms in production on a cloud provider such as GCP, AWS, or Azure, in both batch and streaming: you have operated infrastructure for each, not only one. - Experience designing data platforms at scale: storage and compute choices, multi-team access, reliability, and cost. - Experience operating cloud data warehouses and real-time stores such as BigQuery and ClickHouse. - Experience operating streaming infrastructure such as Pub/Sub, Kafka, Dataflow, or Flink, including retention, schema evolution, replay, and lag monitoring. - Experience operating batch infrastructure: orchestration (Dagster or Airflow), CI/CD, and environments. - Infrastructure as code with Terraform. - Experience with access control and data governance, such as IAM, column- or row-level security, and PII handling. - Strong Python and SQL. - Proficiency using AI tools to learn new skills and accelerate your work, while taking responsibility for checking the output. Nice to have - ML infrastructure experience, such as feature stores, Vertex AI, or model serving. - Experience in regulated environments such as payments, banking, PCI, or SOC 2. - Experience with data catalogs and lineage tools. - Experience with cost optimization in BigQuery, ClickHouse, or Snowflake. - Experience with CDC tools such as Datastream or Debezium. Things that enable a fulfilling, healthy and happy experience at Rain: Flexible time off 🌴 Unlimited vacation can be daunting, so we require Rainmakers to take 10 days minimum for themselves. Flexible working ☕ We support a flexible workplace – work from home, come into an office, or both. We want everyone to work in an environment where they're their most confident and productive selves. New Rainmakers receive a stipend to set up a comfortable home workspace. Easy to access benefits 🧠 For US Rainmakers, we cover 95% of your health, dental, and vision plan costs and 90% for your dependents, plus a 100% company-subsidized life insurance plan. Retirement goals💡 Plan for the future with confidence. We offer a 401(k) with a 4% company match. Equity plan 📦 Every Rainmaker gets an equity option plan so we all benefit from our success. Health and Wellness 📚 High performance begins from within. Rainmakers receive a monthly stipend to be used for eligible health and wellness spending like gym memberships/fitness classes, massages, acupuncture - whatever recharges you! In-office meals 🍜 Rainmakers working from the office enjoy lunch and dinner on us, covered with a DoorDash credit. Team summits ✨ Summits play an important role at Rain. Time together helps us build relationships and a common destiny. Expect team and company offsites, both domestic and international.

Location: San Juan, Puerto Rico; New York, NY; District of Columbia; Europe | Spain Workplace: OnSite About the Company Rain is the global stablecoin payments platform for enterprises, neobanks, platforms, developers, and AI agents. Our technology allows partners to move, store, and use stablecoins instantly and compliantly through global payment cards, rewards, on/offramps, wallets, and cross-border rails. As both a Visa and Mastercard Principal Member, Rain issues cards that work at more than 175 million merchant locations in over 220 countries and territories. Built natively for stablecoins and trusted by more than 100 organizations worldwide, Rain delivers secure, scalable infrastructure that makes money move freely and instantly around the world. You will have the opportunity to deliver massive impact at a hypergrowth company backed by some of the top investors in fintech, crypto, and SaaS. In January 2026, we closed a $250M Series C led by ICONIQ, valuing Rain at $1.95B, with Sapphire Ventures, Norwest, Galaxy Ventures, Dragonfly, Bessemer Venture Partners, FirstMark, Lightspeed, and Endeavor Catalyst also participating. If you're curious, bold, and excited to help shape a borderless financial future, we'd love to talk. Our Ethos We believe in an open and flat structure. You will be able to grow into the role that most aligns with your goals. Our team members at all levels have the freedom to explore ideas and impact the roadmap and vision of our company. About the role Rain is building payments and stablecoin infrastructure. Every transaction generates data across our system. We’re looking for an Analytics Engineer, Finance to own the data layer Finance runs on: model it, reconcile it against source systems, test it, automate it, and make it self-serve. You’ll partner with Finance and Accounting and the data team to make sure every number we report ties back to its source. We’re looking for someone with high agency and urgency who owns problems end to end, digs into discrepancies until the numbers tie out, and communicates clearly when something is uncertain. We care less about where you trained and more about what you’ve built. At Rain, we’re builders who use AI to automate repetitive work. That changes what data roles look like: where a data scientist used to only analyze and an analyst used to only build dashboards, here everyone models data, writes production-quality code, and automates their own workflows. You own the result, including checking what the AI produces. For this role, that means building trusted models and automating the reconciliations and reporting Finance depends on. What you’ll do - Build and own models for Finance: ledger, settlements, card transactions, invoicing, fees, and collateral, with clear grain and consistent definitions. - Build and run reconciliations between internal systems and external sources (card networks, processors, banks, partners); investigate breaks and fix the root cause. - Support month-end close and audit readiness with validated, documented outputs Finance can trust. - Automate recurring Finance reporting and deliveries (scheduled reports, exports, and alerts) so close and partner reporting run without manual work. - Add data quality tests and alerts so issues are caught before Finance sees them. - Partner with Finance to define metrics such as revenue, costs, volume, and contribution profit, and make them reusable across teams. - Build self-serve reporting so Finance can answer recurring questions independently. - Work with data and platform engineers on ingestion and source changes, following Rain’s data standards and access policies. What you’ll need - At least 3 years of experience in analytics engineering, software engineering, or analytics with a strong data modeling focus. - Proficiency using AI tools to learn new skills, navigate unfamiliar domains, and accelerate your work, while taking responsibility for checking the output. - Strong SQL in a modern data warehouse such as BigQuery, Snowflake, or Redshift, including complex joins, window functions, and incremental logic. - Hands-on dbt experience: data modeling, testing, documentation, version control, and code review. - Experience reconciling data across systems and explaining differences down to the row. - Familiarity with financial metrics and processes, such as revenue and costs, financial statements, reconciliation, or monthly close. - Strong attention to detail: you validate results against source systems and explain assumptions, tradeoffs, and uncertainty. - Ability to work independently and collaboratively in a fast-moving startup, communicating clearly with technical and nontechnical partners. Nice to have - Experience in payments, card issuing, fintech, or stablecoins, such as settlement files, ledgers, or interchange. - Experience with BI as code, such as Lightdash, Looker, or Omni. - Python or another scripting language for automation and data checks. - Experience working directly with Finance or Accounting teams. - Experience with orchestration and ingestion tools such as Dagster, Airflow, Meltano, Fivetran, or Datastream. Things that enable a fulfilling, healthy and happy experience at Rain: Flexible time off 🌴 Unlimited vacation can be daunting, so we require Rainmakers to take 10 days minimum for themselves. Flexible working ☕ We support a flexible workplace – work from home, come into an office, or both. We want everyone to work in an environment where they're their most confident and productive selves. New Rainmakers receive a stipend to set up a comfortable home workspace. Easy to access benefits 🧠 For US Rainmakers, we cover 95% of your health, dental, and vision plan costs and 90% for your dependents, plus a 100% company-subsidized life insurance plan. Retirement goals💡 Plan for the future with confidence. We offer a 401(k) with a 4% company match. Equity plan 📦 Every Rainmaker gets an equity option plan so we all benefit from our success. Health and Wellness 📚 High performance begins from within. Rainmakers receive a monthly stipend to be used for eligible health and wellness spending like gym memberships/fitness classes, massages, acupuncture - whatever recharges you! In-office meals 🍜 Rainmakers working from the office enjoy lunch and dinner on us, covered with a DoorDash credit. Team summits ✨ Summits play an important role at Rain. Time together helps us build relationships and a common destiny. Expect team and company offsites, both domestic and international.

Location: New York City, NY Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Location: Reddit has a flexible-first workforce. Don't live near our New York office? No worries: you can work remotely from anywhere on the US East Coast (Eastern Time). The Ads Foundational Representations (AFR) team develops signals and representations of Reddit’s core entities (ads, posts, users, and so on), capturing the semantic, contextual, and behavioral information that Reddit Ads needs. We work on building embeddings to understand content and users' interests based on the content they engage with. Our team has the potential to highlight one of Reddit's biggest differentiators: genuinely curated, high-quality, extremely relevant, and daily updated organic content. We are a Machine Learning/Data heavy team with a focus on the following areas: Multimodal & Content Embeddings - Make sense of organic (posts, comments, subreddits) and promoted (ads, shopping products, their landing pages) text and media content by embedding them into a shared space. Contextual and Behavioral Relevance - Working with Product & Data Science, establishing definitions of what ads are relevant to users and the content we show them next to, building metrics and fine-tuning embeddings to better reflect relevance. Knowledge Graph Embeddings - Building representations for the Knowledge graph entities, e.g., intellectual properties/brands, to be used for high-precision targeting & business insights. User Intent Modeling - Leveraging various techniques to introduce user representations based on the content they interact with: batch & real-time sequence modeling, LLM summarization, etc. LLM-based Representations - Leveraging LLMs, VLMs, and foundational models to build complex representations of Reddit entities that improve ranking outcomes The signals and features we create become a key piece in the Ads Delivery funnel, from targeting to the auction, as well as the Business Insights product and other advertiser-facing products such as Creative generation and optimization. As a Staff ML Engineer , you’ll be in charge of setting the technical direction of multiple pillars the team owns. You will lead cross-functional ML projects end to end - from high-level business gap analysis to engineering execution. Roughly 50% of your time will be spent on technical leadership and mentorship (driving strategy & designs, cross-functional collaboration, raising the quality bar), another 50% being individual hands-on work (data analysis & engineering, modeling & automation). Responsibilities Providing technical leadership and mentorship to MLEs in the team: driving designs & their review, establishing best practices in analysis, modeling and engineering, keeping the bar high. Working closely with team/org leadership developing technical strategy for content-based embeddings & relevance for Ads. Developing new or iterating on existing embedding models for advertising use cases, ranging from aggregation pipelines to two-tower architectures and sequence models. Working with local and 3rd-party LLMs/VLMs: extract representations, develop evaluation methodologies, prompt tune and fine-tune large models to build state-of-the-art embeddings. Building data processing and inference pipelines for the models we develop. Qualitative and quantitative evaluation of the various features we develop, end-to-end experimentation from internal benchmarks to downstream recommender system offline metrics to online experiments. Ensuring the reliability, scalability, and performance of the ML systems by writing automated tests, monitoring performance, and implementing best practices for model management. Participating in modeling and coding reviews: You will review work by other team members and provide feedback to ensure that it meets the team's standards for quality and performance. Collaborating with cross-functional teams to understand business requirements and translate them into technical solutions. Required Qualifications: 7+ years of hands-on experience with the full lifecycle of designing, training, evaluating, testing, and deploying industry-level models. Demonstrated Staff-level technical leadership: mentoring engineers, driving standards and bar raising, leading complex cross-functional projects: from requirements, design to cross-team/functional alignment and execution without direct people-management authority. Excellent communication skills, with the ability to translate complex technical concepts to different audiences, both verbally and in writing. Strong track record of working on content rich NLP/CV problems at scale, and using embeddings as a tool to solve them. Established data-driven approach for ML system development. Excitement about working with data and readiness to look behind the metric numbers. Familiarity with the Ads domain and/or Search/Recommender systems. Experience with mainstream DL frameworks: PyTorch or TensorFlow. Preferred Qualifications: Experience with our stack (Python, Pytorch, Airflow, BigQuery, Ray, k8s, kafka, GCP) Tech leadership experience: mentoring junior engineers and leading complex projects. Hands-on experience with using/fine-tuning/building LLMs. Benefits: Comprehensive Healthcare Benefits and Income Replacement Programs 401k with Employer Match Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support Family Planning Support Gender-Affirming Care Mental Health & Coaching Benefits Flexible Vacation & Paid Volunteer Time Off Generous Paid Parental Leave Pay Transparency: This job posting may span more than one career level. In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/ . To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below. The base salary range for this position is: $230,000 — $322,000 USD In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews. During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable.  We will not sell your personal information or disclose it to any third party for their marketing purposes.  We will delete any recording of your interview promptly after making a hiring decision.  For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors . Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve.  Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.

Location: ES - Barcelona, Spain Scopely is looking for a Sr. Data Analyst to join the Scrabble Analytics team in Barcelona on a hybrid basis! At Scopely, we care deeply about what we do and want to inspire play every day - whether in our work environments alongside our talented colleagues or through our deep connections with our communities of players. We are a global team of game lovers who are developing, publishing, and innovating the mobile games industry, connecting millions of people worldwide daily. Scrabble® GO is one of our casual free-to-play mobile games and is the modern version of the world’s favorite word game! The team is based in Europe and the US, and works every day to create captivating new experiences for our players. What You’ll Do Analyze large, complex datasets representing the behavior of millions of players to address strategic and operational business questions. Transform data into actionable insights that drive meaningful business decisions. Design and deliver engaging dashboards and reports that provide clear visibility into game performance metrics and player behavior for key stakeholders. Design, implement, and evaluate A/B tests to measure feature performance, optimize player experiences, and guide data-informed decisions. Partner with cross-functional teams to align priorities, influence roadmap decisions, and ensure analytics is central to shaping the player experience. What We’re Looking For Intellectual curiosity, analytical rigor, adaptability, and the ability to innovate while working both independently and collaboratively. Extensive experience as a Data Analyst, ideally in analysis, BI, consulting, or a scientific role. Experience in gaming, tech, or entertainment is a plus. Strong presentation and storytelling skills, with the ability to make complex results accessible across the organization. Critical thinking and problem-solving capabilities with strong communication skills. Proficiency in SQL and data visualization tools (e.g., Looker, Tableau, Power BI, or QlikView). Strong working knowledge of Excel/Google Sheets. Bachelor’s degree in a quantitative or scientific field (e.g., Mathematics, Statistics, Economics, Computer Science, Engineering, Physics, or related). Advanced degrees are a plus. A passion for mobile games and curiosity about player behavior and industry trends. Bonus points Experience with Python or R for data analysis. Familiarity with cloud-based data warehouses (e.g., BigQuery, Snowflake, Redshift). Experience in the gaming industry or related digital entertainment sectors. At Scopely, we create games for everyone - and want to ensure that the people behind our games reflect that!   We are committed to creating a diverse, supportive work environment where everyone is treated with respect. We are committed to providing equal employment opportunities and welcome individuals from all backgrounds to join us & embrace the adventure! About Scopely Scopely is a leading video game and global interactive entertainment company, home to many of the world’s most beloved and enduring experiences, including two of the most successful mobile games of all-time “MONOPOLY GO!” and “Pokémon GO,” along with “Stumble Guys,” “Star Trek™ Fleet Command,” “MARVEL Strike Force,” “WWE Champions,” the Scrabble® franchise, “Yahtzee® With Buddies,” and many others. Across mobile, web, PC, and console, Scopely creates, develops, publishes, and live-operates one of the most diversified and award-winning portfolios in the games industry — bringing hundreds of millions of players together through a shared love of play. Founded in 2011, Scopely is powered by its exceptional team — including thousands of world-class gamemakers around the globe, a distinctive tenet-driven culture, and its proprietary technology platform, Playgami. Together, these strengths have fueled Scopely’s position as the #1 mobile games company in the U.S. and #2 globally, generating more than $10 billion in lifetime revenue. Whether building global sensations like “MONOPOLY GO!” from the ground up, or expanding through strategic acquisitions, including the FoxNext, GSN, and Scopely Explore games businesses — Scopely consistently delivers experiences players love today and return to for years to come. Recognized multiple times as one of the "100 Most Influential Companies in the World" by TIME magazine and one of Fast Company's "World's Most Innovative Companies" and “Best Workplaces for Innovators,” Scopely believes that video games can be a force for good — creating meaningful connections, vibrant communities, and making life better through play. Scopely has global operations and partners across four continents in more than a dozen countries worldwide. For more information, visit: https://www.scopely.com/ . Notice to Candidates: Scopely will never request payment or financial information during the application or hiring process. Please apply only through our official website and verify that all Talent Partner communications come from an email address ending in @ scopely.com . Should you have any questions or encounter any fraudulent requests/emails/websites, please immediately contact recruiting@scopely.com. Our job applicant privacy policies are available here: California Privacy Notice and EEA/UK Privacy Notice . Employment at Scopely is based solely on a person's merit and qualifications. Scopely does not discriminate against any employee or applicant because of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), or any other basis protected by law. We also consider qualified applicants with arrest or conviction records, consistent with applicable federal, state and local law.

Location: Riga, Latvia Workplace: hybrid Are you ready to join our digital revolution journey?    At Aleph, we’re not just part of the digital advertising landscape—we’re shaping its future. Representing the world’s leading platforms, including TikTok, Amazon, Google, and nearly 55 others, we operate in 130+ markets across new and existing geographies.   Our mission is to empower advertisers and brands to unlock the full potential of these platforms' advertising capabilities. By fostering long-lasting partnerships, we create limitless opportunities for people and businesses to advertise effectively at both local and global levels.   With a presence spanning continents, Aleph offers you the chance to be part of a fast-growing, innovative team where your work makes a direct impact. If you’re ambitious, forward-thinking, and eager to thrive in a dynamic, global environment, Aleph is the perfect place to build your career. What you'll do: Advertising data and business analysis ● Analyze performance: Work with digital advertising metrics such as spend, impressions, clicks, conversions, campaign performance, and revenue to identify trends, anomalies, differences, and possible drivers across platforms and markets. ● Connect context: Combine platform, CRM, financial, and internal operating data to support questions across markets, advertisers, products, and teams. ● Explain results: Translate findings into concise observations and useful visualizations, clearly distinguishing facts, assumptions, and data gaps. Reporting, data preparation, and quality ● SQL and cloud data: Work directly with database tables using SQL to query, join, clean, and organize datasets in Google BigQuery or comparable cloud data environments; help maintain straightforward reporting views and transformations. ● Support BI reporting: Build and maintain reporting datasets, dashboards, and recurring reports using agreed definitions in Looker Studio or comparable tools. ● Validate reliability: Check completeness, duplicates, consistency, unexpected changes, and reconciliation against source totals; document and escalate issues. Data connections and lightweight automation ● Follow the data: Understand how data from digital advertising platforms, CRM, and internal sources reaches cloud data environments such as BigQuery and feeds reports; help check scheduled refreshes and investigate missing or delayed data. ● Support connections: Assist colleagues with existing advertising-platform data connections and basic API-related issues, such as changed fields or incomplete responses. ● Simplify repeatable work: Improve recurring data preparation and validation primarily through SQL; experience with Python, another scripting or programming language, or practical automation tools is useful but not central to the role. ● Provide continuity: Learn and document selected BI data refresh and preparation routines so they can be supported when the main technical colleague is unavailable; escalate infrastructure issues to Data or IT Collaboration and professional growth. ● Clarify requirements: Work with analysts and business colleagues to understand the question, expected outputs, and suitable data sources. ● Document work: Keep data sources, logic, dependencies, procedures, and known limitations understandable and reusable. ● Develop capabilities: Build on practical statistical understanding and gradually apply approaches such as segmentation, anomaly detection, forecasting support, and introductory predictive analysis where they improve business decisions. What are we looking for: Experience and education ● Relevant experience: 1+ year of hands-on experience in digital marketing analytics, performance reporting, business intelligence, or data analysis involving direct work with databases. Experience gained in agencies, relevant internships, or substantial practical projects is welcome. ● Preferred background: Experience in a media agency, performance marketing agency, digital agency, ad-tech company, or advertising analytics team is a strong advantage, particularly if it involved working directly with digital advertising platform datasets rather than only finished dashboards. ● Education: Degree or equivalent practical experience in analytics, statistics, mathematics, computer science, engineering, economics, or a related field. A background in statistics or quantitative analysis is a particular advantage. Capabilities ● SQL – essential: Practical ability to query and combine structured data independently using SQL (e.g., joins, filters, aggregations, and basic transformations). Advanced SQL expertise is not expected, but database work should be familiar. ● Cloud data platforms: Hands-on experience with Google BigQuery or a comparable cloud data warehouse or analytics environment, such as Amazon Redshift, Snowflake, or Azure-based data solutions, is highly valued. No specific cloud vendor experience is required ● Reporting and analysis: Can prepare datasets and work with reporting tools such as Looker Studio, Power BI, Tableau, or Looker; understands campaign metrics and knows how to investigate inconsistent results ● Database understanding: Understands database tables, relationships, refreshes, and the path from source platforms into reporting datasets; has worked with underlying data rather than only ready-made dashboards. ● Digital platform data: Experience working with advertising or measurement data from platforms such as Google Ads, Meta Ads, TikTok Ads, Microsoft Advertising, Amazon Ads, DV360, or GA4 is a strong advantage. Familiarity with one or several platforms is sufficient; expertise across all platforms is not expected. ● Analytical and statistical thinking: Comfortable with data distributions, averages, variation, trends, comparisons, and basic statistical reasoning; able to spot anomalies, challenge assumptions, and explain results in business terms. ● Communication and ownership: Clear English, careful documentation, collaborative working style, and willingness to learn from both business and technical colleagues ● Additional technical skills: Exposure to Python, JavaScript, Java, R, or another programming or scripting language, as well as APIs, or basic automation, is a plus rather than a requirement. Practical curiosity and willingness to learn are more important than a particular language. Measures of success: ● Trustworthy output: Reports and datasets are accurate, consistent, traceable, and delivered on time ● Useful insight: Analysis identifies meaningful performance signals and supports practical business decisions ● Operational resilience: Selected BI data connections and refreshes are monitored, documented, and supported with appropriate escalation ● Efficiency: Manual preparation or recurring reporting effort is reduced through safe, maintainable improvements ● Growth: Increasing independence with SQL, cloud-based datasets, advertising-platform data structures, and selected BI workflows, with opportunities to develop toward advanced analytics. Why Join Us?   Aleph is a place of many cultures, perspectives, and talents. We support each other, creating an environment of giving and receiving. We value partnership and communication because we believe it takes a group of people to achieve great things. We are energized by our ever-changing industry, our curiosity keeps us learning and seeking out new opportunities.     We stay flexible and adaptable, and believe in moving with the speed of change. We encourage everyone to strive for more, providing our internal talent with growth opportunities and the ability to learn together.    #ALEPH

Location: United Kingdom; Spain; Germany Workplace: remote Help Us Build The Future of Travel At Airalo, we're making it easier for people to stay connected wherever they travel. As the world's first eSIM store, we help millions of travelers access affordable mobile data in 200+ countries and regions around the world. Today, we're a team of 400+ people across 60+ countries, building a product used by travelers every day. We've grown quickly, but we've worked hard to keep what matters: trust, ownership, and the freedom for people to do great work without unnecessary layers or bureaucracy. We're fully remote by design, genuinely global, and united by a shared mission to make travel simpler for everyone. Your Next Destination Location: Remote. Contract: Full-time, permanent. Benefits: Learn more about our benefits here in this link - https://airalo-public.notion.site/Benefits-25396a97ffca81fb9bc1f0be479f1be3?pvs=74  Languages: English is our main working language day to day, so you'll need to be comfortable communicating in it both in meetings and async. What You'll Do Support our marketing attribution models and methodology: review how conversions are credited across channels, reconcile platform-reported and first-party numbers, and keep the approach trusted and documented. Design and maintain the marketing data models behind measurement (spend, attribution, orders and customer cohorts) with Analytics Engineering, with clear definitions, tests and documentation. Support Growth and Marketing with ad-hoc and core analytics, such as campaign and market performance, self-serve dashboards and AI-assisted analytics. Design and run geo experiments from simulation-based power analysis and market selection to success criteria and read-out, working with the marketing performance team. Co-own a prioritised quarterly incrementality test roadmap across channels and markets, ranked by decision value, cost, feasibility (including properly powered tests) and learning, and track each test through to a decision. Handle spillover, seasonality and small-market noise, and report incremental CAC and incremental ROAS with honest uncertainty. Turn test results into investment guidance: estimate marginal returns and saturation by channel and market, and recommend where the next dollar should go and where to pull back. Help set and document our causal measurement standards: which method when, what counts as sufficient evidence, and how results calibrate attribution and MMM for budget allocation. Defend the framework under challenge from channel owners and leaders, and pressure-test platform claims. Guide Growth, Acquisition and Finance from business question to testable hypothesis to budget decision, and build literacy on attributed versus incremental performance. Build reusable experiment tooling and templates, work with Analytics Engineering and MarTech on the data experiments needed, and document every test and decision as you build this capability from scratch. What You'll Bring 3+ years of experience in marketing measurement (attribution, incrementality or marketing mix modelling), with a track record of analysis that changed real budget decisions. Solid grounding in causal inference and experimental design: randomised and quasi-experimental methods such as synthetic control and difference-in-differences, simulation-based power analysis to size and design tests, and knowing when each approach breaks. Strong statistical judgement: you can quantify uncertainty, explain it simply, and resist overclaiming. Hands-on experience with marketing attribution models and their limits, including reconciling platform-reported results with first-party data. Familiarity with how experiments calibrate MMM and attribution, and with marginal-return and budget-optimisation thinking (saturation, diminishing returns). Expert SQL and Python, production-quality code, a modern warehouse (BigQuery or Snowflake) and a BI tool such as Lightdash or Looker. Strong data modelling skills: designing clean, tested and documented models (dbt or similar) for marketing spend, attribution and customer data, and working closely with Analytics Engineering. Strong core analytics skills: marketing and customer metrics (CAC, LTV, retention, funnel and cohort analysis), dashboards and self-serve BI, and the judgement to prioritise ad-hoc requests alongside the test roadmap. Proven ability to influence senior stakeholders: you hold a position under challenge, have shaped a roadmap, and say no with a clear rationale. Comfortable with ambiguity and with data that is still improving: you're a proactive self-starter who is happy to create a new process or capability in a small, fast-growing team. Why People Join Us We started Airalo to make staying connected effortless, wherever you are in the world. Today, millions of travelers rely on our eSIMs, and many of the people building the product were customers first. Our team spans 60+ countries, united by a shared belief that great work happens when people are trusted to own what they do. There's trust to own what you do, space to focus without constant layers of process, and a clear sense of what you're responsible for from day one. As Airalo continues to grow, so do the opportunities to learn, take on new challenges, and make a real impact - from anywhere in the world. Before You Hit Apply By applying, you acknowledge and agree that, in case of successful application, Airalo may request to run background checks as a condition for entering into an agreement with you. Rest assured that these checks will only occur upon your prior consent and at the end of the selection process, and will be strictly limited to what is allowed under the laws that are applicable to you. All data that you share or that we collect in connection with such checks will be processed in accordance with our Privacy Policy, available here: www.airalo.com/more-info/privacy-policy?srsltid=AfmBOooBT0rXAj1FaNelZ3VfN0wvhwzvAoxdtHnOKSVETpiSjiXVuycy    We sincerely thank all applicants in advance for submitting their interest in this opportunity. Airalo is an equal-opportunity employer and values diversity, equity & inclusion. We do not discriminate on the basis of race, religion, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We are committed to providing reasonable accommodations upon request for individuals with disabilities throughout our job interview process. At Airalo, we believe in roaming-free recruitment. Just as we provide clear connectivity for travelers, we provide clear salary ranges for our candidates. 🌍 This role is remote and open to candidates across our supported locations in Europe. The range below reflects the full salary range for this role across the countries where it’s available: 📍UK: £64,000 - £96,000 📍Spain: €62,000- €93,000 📍Germany: €68,000- €102,000 Your Home Destination: Local market rates and cost of living vary, so your specific range depends on where you’re based. Most people join in the first half of the band, which leaves you plenty of room to grow, and you’ll see exactly how that looks from day one. In exceptional cases, where a candidate’s skills and experience clearly exceed what the role requires, we’re happy to talk about going higher. We’ll walk through your range together on your first call with our Talent team, so we’re all aligned for takeoff!

Location: Remote, Global Workplace: Remote ABOUT SUPABASE Supabase is the Postgres development platform, built by developers for developers. We provide a complete backend solution including Database, Auth, Storage, Edge Functions, Realtime, and Vector Search. All services are deeply integrated and designed for growth. ABOUT THE ROLE We're looking for an Engineering Manager to lead the Pipelines team at Supabase. Supabase Pipelines is a managed change data capture product. It copies the tables you select from Supabase Postgres to other systems, then streams later changes. The product is in public alpha, with BigQuery, ClickHouse, DuckLake and Snowflake destinations. Pipelines uses Postgres logical replication and Supabase ETL, our open source replication engine written in Rust. The team works close to the database. That means replication slots, WAL retention, initial table syncs, and the load they place on a customer's source database. The team also builds and runs the destination connectors. Correctness, ordering and recovery matter there as much as speed. The Engineering Manager is a people, delivery and technical role. We don't expect you to write production code. We do expect you to join design discussions and help set the bar for engineering quality, testing and operations. WHAT YOU’LL BE RESPONSIBLE FOR Team & People - Build a healthy, high-trust team culture in a remote-first, globally distributed environment. - Run 1:1s, performance management, career development, and onboarding for your direct reports. - Handle people admin (leave, time off, etc.) for your team. Hiring - Own the hiring plan for your team and act as Hiring Manager. First round of interviewer for all roles on the team. - Partner with Talent Acquisition to source, interview, and close strong candidates. - Contribute to headcount planning, org design, and the evolution of engineering leadership at Supabase. Delivery & Roadmap - Own the team's roadmap and project management (Linear), driving accountability and clear milestones. - Manage workflow intake and Slack triage. These are the team’s primary inboxes for cross-team requests. You decide what gets routed where, prioritized, or pushed back on. - Own the team's weekly updates and keep stakeholders aligned without creating overhead. - Organize effort against support tickets and maintain the team's SLO. - Surface risks, dependencies, and tradeoffs early and clearly to leadership. Incident Commander - Train as an Incident Commander. Drive coordination, resolution, and post-incident follow-up. - Lead blameless post-incident reviews YOU MIGHT BE A GOOD FIT IF YOU - Have 5+ years of engineering background, with enough depth to be credible with engineers building complex systems. - Have 3+ years managing remote engineering teams. - Have managed a team that built and ran data pipelines, change data capture, replication or streaming systems. - Have strong technical credibility in data systems. We look for delivery guarantees, ordering, idempotency, schema changes and backfills. - Know Postgres replication well, including logical replication, the WAL and replication slots, and how they affect a production database. - Know analytical destinations such as BigQuery, Snowflake, ClickHouse or lakehouse table formats like Iceberg. - Have led a team through production incidents on a system that holds customer data. You ran the follow-up work and kept the review blameless. - Have shipped a developer-facing data product to customers outside your company. - Have experience with Rust (not required but a plus) - Have managed remote, globally distributed teams that work asynchronously across disparate time zones. - Are technical enough to be credible with strong engineers, but genuinely passionate about people management. This is the work you want to do, not a track you're settling for. - Build psychological safety and a feedback culture. You give feedback often and in the moment, ask for it back, and create space for the team to do the same. - Operate as a multiplier. You help individuals achieve more than they could alone, and you don't need to be the best technical voice in the room. - Coach rather than direct. You remove blockers, connect people to context, and trust your engineers to own how the work gets done. - Have a real track record of performance management and can speak to specific examples of difficult conversations. - Are comfortable with ambiguity and can build structure where there isn't much. - Communicate clearly and write well. You default to async and written, set context early, and surface risks early. - Are collaborative, low-ego and adaptable. You thrive with high-autonomy senior engineers who don't need you to be the smartest person in the room. WHAT WE OFFER - Fully Remote We hire globally. We believe you can do your best work from anywhere. There are no Supabase offices, but we provide a WeWork membership or co-working allowance you can use anywhere in the world. - ESOP Every team member receives ESOP (equity ownership) in the company. We want everyone to share in the upside of what we’re building together. - Tech Allowance Use this budget to set up your ideal work environment—laptop, monitor, headphones, or whatever helps you do your best work. - Health Benefits Supabase covers 100% of health insurance for employees and 80% for dependents, wherever you are. Your wellbeing and your family’s health are important to us. - Annual Off-Sites Once a year, the entire company gathers in a new city for a week of connection, collaboration, and fun. It’s a highlight of our year. - Flexible Work We operate asynchronously and trust you to manage your own time. You know what needs to be done and when. - Professional Development Every team member receives an annual education allowance to spend on learning—courses, books, conferences, or anything that supports your growth. ABOUT THE TEAM Supabase was born-remote and open-source-first. We believe our globally distributed team is our secret weapon in building tools developers love. - ~400 team members - 60+ countries - 20+ languages spoken - Over $1B raised (including our $500M Series F) - 540,000+ community members We move fast, build in public, and use what we ship. If it’s in your project, we probably use it in ours too. We believe deeply in the open-source ecosystem and strive to support—not replace—existing tools and communities.

Kody is looking for a Data Scientist to analyze payment data, build business intelligence dashboards, and support commercial decisions.

* Build and operate batch and incremental ingestion pipelines in Google Cloud to Smartly Data Platform. * Develop Airflow workflows using Python with best orchestration practices, including dag dependencies, retries, backfills, alerting, and recovery.

Миграция attribution-пайплайна на core DWH, витрины в BigQuery, data quality. Стек: SQL (expert), Python, dbt, Airflow, Git.

Location: Minsk Workplace: onsite National Retail Solutions (NRS) is a leading provider of point-of-sale, payment, and digital solutions to tens of thousands of independent retailers across the United States and Canada. Processing millions of transactions daily across a rapidly growing network of high-volume retail terminals, NRS generates massive volumes of operational data. To empower our retailers and internal teams with instant insights, NRS is building a state-of-the-art, high-throughput Real-Time Reporting Engine powered by ClickHouse. This strategic initiative involves modernizing our data infrastructure, building scalable analytical pipelines, and delivering sub-second reporting dashboards for large-scale transaction datasets. We are seeking an experienced Technical Project Manager (Data & Reporting Platform) based in Minsk to join our distributed engineering team. In this role, you will lead the end-to-end delivery of our core ClickHouse real-time reporting platform, coordinating cross-functional efforts across backend engineers (Golang/Node.js/PHP), database architects, data engineers, QA, and frontend developers (Vue.js). The ideal candidate possesses strong technical project management fundamentals, a solid grasp of data systems/ETL workflows, and naturally leverages AI workflows (Claude, Gemini) to optimize sprint planning, write technical specifications, streamline documentation, and track technical deliverables. This role requires 3 days a week in-office work at our Minsk office facility to collaborate in person with our engineering team, along with regular remote collaboration with teams in Israel and the U.S. Responsibilities: Program Execution & Technical Project Delivery Lead end-to-end project execution for our ClickHouse real-time reporting platform, managing schedules, sprint backlogs, dependency mapping, and technical milestones. Partner closely with backend developers, data engineers, and UI teams to plan and execute high-throughput data pipelines, data aggregation flows, and reporting API deployments. Manage technical risks, identify pipeline bottlenecks, resolve execution blockers, and establish clear criteria for platform stability and performance testing. Act as a technical bridge between Product Management, System Architects, and Engineering teams to translate complex reporting requirements into clear user stories and technical tasks. Leverage modern AI productivity tools (Claude, Gemini) to accelerate sprint documentation, analyze project risks, summarize technical alignment meetings, and draft comprehensive project specs. Metrics, Stakeholder Management & Status Reporting Establish and maintain KPIs, execution velocity metrics, and project health dashboards in Jira/Confluence. Provide weekly progress updates to senior leadership, including the VP of Technology, CTO, and key business stakeholders. Oversee SLA requirements, data delivery timelines, and release readiness checklists across global teams. Organize and facilitate cross-functional release management, ensuring smooth rollouts with zero downtime for reporting services. Data Integrations & Cross-Team Collaboration Oversee data integration initiatives with third-party platforms, external data feeds, and internal microservices. Understand partner technical specifications, API structures, data schema expectations, and support escalation paths. Lead Agile ceremonies (Sprint Planning, Daily Standups, Backlog Grooming, Retrospectives) for distributed engineering groups across time zones. Required Qualifications: 5+ years of Technical Project Management experience leading complex software development or data engineering initiatives. Proven Data & Platform Project Management Experience: Hands-on experience delivering projects focused on databases, business intelligence (BI), analytics, ETL/data pipelines, or high-throughput reporting systems. Agile & Jira Mastery: Advanced proficiency in Jira (Scrum/Kanban management, roadmapping, custom workflows, automation) and Confluence documentation. Strong AI Integration Capabilities: A habitual and demonstrated workflow using AI assistants (Claude, Gemini) to optimize project planning, write specifications, summarize requirements, and improve delivery velocity. Technical Understanding of Systems Architecture: Solid conceptual understanding of microservices, REST/gRPC APIs, SQL/database architectures, CI/CD pipelines, and cloud environments (AWS). Scope & Risk Management: Proven ability to manage technical debt, negotiate scope trade-offs with product owners, and clear complex engineering blockers independently. Cross-Functional & International Experience: Exceptional team leadership skills with experience working alongside global teams in the U.S. and Israel. Strong Communication: Excellent spoken and written English, comfortable facilitating technical design discussions and executive briefings. Nice to Have: Experience managing projects involving ClickHouse or other columnar/OLAP data stores (Snowflake, BigQuery, Redshift). Background in managing high-availability, low-latency financial, transaction, or POS reporting environments. Familiarity with data visualization tools or reporting dashboards (Grafana, Tableau, Metabase, custom Vue.js dashboards). PMP, PMI-ACP, CSM (Certified Scrum Master), or equivalent Agile/Project Management certifications. Work Schedule & Location: Location: Minsk, Belarus (Office). In-Office Requirement: 3 days per week at our Minsk office facility. Time Zone Overlap: At least 3 hours of daily overlap with U.S. Eastern Standard Time (EST). What We Offer: A central role in delivering a high-impact, real-time data engine for the U.S. retail tech market. Direct collaboration with highly skilled engineering and product leadership in Minsk, Israel, and the U.S. Clear career advancement opportunities within a rapidly scaling data platform team. Competitive compensation package. Our benefits: Hybrid work opportunity! Modern office with free parking in the very center of Minsk. An exciting and challenging job with talented people around. Competitive salary and growth opportunities. Really good hardware. 26 vacation days & 5 fully covered sick days without sick leave required per year. Compensation for professional training, seminars, and conferences. Sports activities reimbursement and loyalty program. Medical insurance. Referral program – get rewarded for helping us grow the team with talented people. Company-supported English classes to enhance your professional growth. A few words about us: IDT Corporation is a global communications company founded in 1990 and headquartered in Newark, New Jersey. We are industry leaders in prepaid communication and payment services and one of the largest international voice carriers. We are listed on the NYSE, employ over 1800 people across 20 countries, and have over $1.5 billion in revenues.We are not ”another big IT corporation”— we encourage and support in-house entrepreneurs in developing their ideas into business actions.   Our National Retail Solutions brandprovides a sales management system and POS equipment to small and medium-sized businesses. With the help of NRS, business owners can solve a management problem: the product includes integrated advertising, data analysis, and payment processing. NRS is now expanding into a completely new vertical: restaurant technology.We are building a brand-new Restaurant POS platform, a modern and highly capable system designed specifically for restaurant operations. This is one of the most significant product expansions in NRS history and will open a major new market for the company.This is a real opportunity to help build something new and important.

Location: Intellias Meet your recruiter Bohdana Rubets bohdana.rubets@intellias.com https://www.linkedin.com... Vacancy details Data Engineering Data Engineer Senior Bulgaria, Croatia, Poland Remote APPLY NOW REFER A FRIEND Let’s breathe life into great tech ideas! With 3,000 people globally, Intellias is a company where benchmark technological solutions are born. Join in and take your part in digitalizing the world. What project we have for you Our client is building the standard path for governed data sharing across product services, analytics, and AI/ML. The Data Platform team owns the contracts, control mechanisms, publication paths, catalog metadata, lifecycle rules, lineage, permissions, and runtime building blocks that make reusable data safe and practical at scale. This is a role for someone who wants to shape a platform early, while working on concrete production problems from the start. Our client already has the production systems, Kafka backbone, PostgreSQL databases, analytical consumers, and AI/ML use cases that need a better data foundation. The challenge is to turn that reality into a standard path that engineers actually want to use. Our first milestone is focused: centrally managed publishing tables in service-owned PostgreSQL databases, captured through Debezium CDC into Kafka, and registered in DataHub with ownership, lifecycle, lineage, and impact-analysis metadata. Longer-term, the platform expands toward self-service data products, governed materialisations, durable shared state, and reusable data across the client’s operational and analytical systems. This is not a role where you only maintain an existing reporting pipeline. You will help design and build the platform path that other engineering teams use when they publish and consume shared data. What you will do Design and build platform services, tools, and workflows for contract-driven data publishing and consumption. Build the first production path for platform-managed PostgreSQL publishing tables, Debezium CDC, Kafka topics, and catalog registration. Create GitOps-style workflows where contracts, schemas, ownership, lifecycle, compatibility, policy metadata, and runtime desired state are reviewed, validated, and reconciled as code. Build tooling that gives product engineers fast feedback before they publish or change data products. Help define how client models data products, publishing contracts, schema evolution, field stability, deletion semantics, access policy, lineage, and cost attribution. Operate and improve the CDC runtime model, including Kubernetes workloads, source-specific isolation, offsets, schema history, heartbeats, signal channels, lag visibility, replay, resnapshotting, and recovery. Integrate platform metadata into DataHub so engineers can discover data products, understand ownership, trace lineage, and reason about the impact of changes. Work with product, infrastructure, data engineering, analytics, and AI/ML teams to make the standard path easier and safer than bespoke point-to-point integrations. What you need for this Strong experience building and operating production software systems, preferably in platform, infrastructure, backend, or data-intensive environments. Deep understanding of distributed systems trade-offs: reliability, idempotency, replay, eventual consistency, ownership boundaries, compatibility, and operational failure modes. Practical experience with PostgreSQL or other relational databases, including schema design, migrations, transactions, replication, or operational performance. Experience with Kafka, event streaming, CDC, Debezium, or adjacent data-movement technologies. Direct Debezium experience is valuable, but strong fundamentals matter more. Experience building software that other engineers use: CLIs, internal platforms, control planes, automation, CI validation, developer tooling, or self-service workflows. Familiarity with Kubernetes and cloud or infrastructure platforms, including runtime isolation, deployment, observability, and operational ownership. Ability to turn ambiguous architectural direction into practical increments, make trade-offs explicit, and deliver useful production systems without waiting for perfect certainty. Clear written and spoken communication in English. This role involves aligning multiple engineering teams around standards, contracts, and ownership boundaries. Nice to have: DataHub or other data catalog, lineage, or governance systems. Open table formats such as Apache Iceberg, object-store-backed data lakes, S3, BigQuery, ClickHouse, or analytical storage systems. GitHub Actions, policy-as-code, infrastructure-as-code, controllers, operators, or reconciliation-based systems. Data contracts, schema registries, Protobuf, Avro, JSON Schema, compatibility checking, field-level metadata, or contract testing. Experience supporting analytics, AI/ML, feature-store-style access patterns, or cross-domain product-service integrations. Experience with JVM languages and Python, TypeScript, Go, or Ruby. What it’s like to work at Intellias At Intellias, where technology takes center stage, people always come before processes. By creating a comfortable atmosphere in our team, we empower individuals to unlock their true potential and achieve extraordinary results. That’s why we offer a range of benefits that support your well-being and charge your professional growth. We are committed to fostering equity, diversity, and inclusion as an equal opportunity employer. All applicants will be considered for employment without discrimination based on race, color, religion, age, gender, nationality, disability, sexual orientation, gender identity or expression, veteran status, or any other characteristic protected by applicable law. We welcome and celebrate the uniqueness of every individual. Join Intellias for a career where your perspectives and contributions are vital to our shared success.

Location: Home-based, Mauritius Workplace: OnSite Company Description We’re http://checkout.comCheckout.com http://Checkout.com. You might not know our name, but companies like eBay, Spotify, Klarna, Uber, and Sony do, because we’re behind many of the digital experiences you use every day. We are where the world checks out, enabling over 10 billion transactions yearly for more than one billion global shoppers. Whether you want to book a holiday, order food, renew a subscription, or check out online, there’s a good chance our tech powers the payments behind the scenes. Our platform helps the most ambitious businesses deliver effortless digital experiences, at scale. If you want to do career-defining work, you’ve come to the right place. We move fast, think globally, and believe great teams are built by hiring exceptional people with conviction, curiosity, and the desire to make an impact. With 20 offices across six continents and London as our HQ, we’re shaping the future of fintech – and we’re just getting started. As a Level 2 Analyst, candidates will be at the heart of our financial ecosystem, ensuring the reliability and efficiency of our payment flows. Candidates will bridge the gap between technical engineering and operational excellence, using data, programming skills, and automation to optimize our core systems. We are looking for an individual with an Athlete Mindset who plans with rigor and constantly seeks more ambitious goals for our monitoring and reporting infrastructure.   KEY RESPONSIBILITIES 1. Operational Discipline & Daily Rigor - Daily Health Checks: As part of Ops engineering team, we are responsible for investigating and remediating transactional failures. We have automated dashboards that run periodically and raise alerts in case of failures - candidates will be expected to master daily checks (investigations and remediation) as this is the core priority of the team. - Incident Response: Candidates are expected to monitor real-time payment alerts, triage performance degradations, and drive issues to closure with a sense of urgency (Pace Matters). - Documentation: We are constantly taking work away from Engineering teams - candidates are expected to maintain and update Standard Operating Procedures (SOPs) for daily tasks, ensuring No Room for Approximation in our execution. 2. Payment Flow Expertise & Scheme Reporting - Lifecycle Management: Maintain a clear understanding of the end-to-end payment lifecycle, including authorization, clearing, and settlement across various payments methods - Card transactions, APMs, PTB etc. - Scheme Reporting: Accurate preparation and submission of reporting for Card Schemes (e.g., Visa, Mastercard), ensuring all data aligns with scheme-specific requirements. Candidates will be expected to investigate how we can reduce manual toil by automating our reporting - aim is 100% accuracy within SLA. - Data Validation: Use a data-driven approach to reconcile internal transaction records against scheme reports to identify and resolve discrepancies. - Compliance Support: Assist in the monitoring of scheme-mandated KPIs and reporting deadlines to ensure the business remains in good standing. 3. Technical & Automation Excellence - Data Analysis (SQL): Candidates are expected to write and optimize SQL queries to extract actionable insights from large datasets when required, keep our monitoring tools (Monte Carlo, Retool, BigQuery) up to date and assist peers with payment related queries. - AI & Automation: Proactively identify repetitive manual tasks and use AI tools or scripting to automate them, supporting our goal to Run Lean. Candidates will be expected to provide tangible results e.g. Number of hours saved, on use of AI and Automation. - Monitoring & Alerting Workflows: Work closely with Engineering to refine and update internal monitoring and alerting workflows, ensuring we maintain an Athlete Mindset toward system health. - Engineering Collaboration: Act as a technical bridge, taking initiative to solve minor bugs or configuration issues, embodying the Be the Owner principle - Continuous Improvement: Adopt a Better Every Day approach by researching new technical tools to enhance monitoring and reporting efficiency. 4. Soft Skills & Team Dynamics - High-Pressure Performance: Candidates should thrive in a fast-paced environment, remaining resilient and focused during critical system incidents (Never Give Up). - Collaboration: Act as a proactive One Team player, sharing knowledge with peers and communicating complex technical issues clearly to non-technical stakeholders. - Accelerated Learning: Demonstrate a desire to learn fast and adapt to new payment technologies and evolving regulatory landscapes. 5. On-Call Duties & Availability - In-Hours Support: Act as the primary technical point of contact for operational health during standard business hours. - On-Call Roster: Participate in a rotating on-call roster, where you may be called upon to support the platform outside of normal working hours to ensure 24/7 reliability. - Weekend & Shift Work: Be prepared to work outside of normal hours and during weekends as required by the business to maintain system uptime and address urgent issues. - Resilience: Demonstrate a Never Give Up attitude, showing resilience and accountability when handling high-priority alerts during off-peak hours. QUALIFICATIONS - Education: Bachelor’s degree in Computer Science, Finance, Engineering, or a related field. - Experience: 2+ years of experience in an operations support or payments-focused role. - Hard Skills: - Proficiency in SQL (data extraction and analysis). - Experience with automation tools or basic scripting (Python/JS is a plus). - Familiarity with AI tools for task optimization and productivity. - Operating Values: You must embody our values by being Fundamentally Positive and acting as an Owner of your work area. Additional Information Bring all of you to work We create the conditions for high performers to thrive, through real ownership, fewer blockers, and work that makes a difference from day one. Here, you’ll move fast, take on meaningful challenges, and be recognized for the impact you deliver. It’s a place where ambition gets met with opportunity, and where your growth is in your hands. We work as one team, and we back each other to succeed. So whatever your background or identity, if you’re ready to grow and make a difference, you’ll be right at home here. It’s important we set you up for success and make our process as accessible as possible. So let us know in your application, or tell your recruiter directly, if you need anything to make your experience or working environment more comfortable. Life at Checkout.com http://Checkout.com We understand that work is just one part of your life. Our hybrid working model offers flexibility, with three days per week in the office to support collaboration and connection. Curious about what it’s like to be part of our team? Visit our Careers Page https://www.checkout.com/careers to learn more about our culture, open roles, and what drives us. For a closer look at daily life at Checkout.com http://Checkout.com, follow us on LinkedIn https://www.linkedin.com/company/checkout/life/ and Instagram https://www.instagram.com/checkout_com/