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Location: Athens, Greece We are seeking a Semantics/Knowledge Graph Engineer to support a complex platform built around RDF data models, SPARQL queries, and structured datasets. You will be responsible for understanding, maintaining, and evolving the semantic layer of the system, working closely with backend engineers and architects. This role suits a specialist who enjoys data modelling, semantics, and knowledge representation in real-world production systems. What You'll Do: Analyse and maintain RDF/TTL data models and vocabularies; Develop, optimise, and maintain SPARQL queries; Support data ingestion, transformation, and validation workflows; Ensure consistency and correctness of semantic data across the platform; Collaborate with backend engineers to integrate semantic logic into application flows; Assist in documenting semantic models, assumptions, and constraints; Participate in troubleshooting data quality and reasoning issues. Requirements 3+ years of experience working with semantic or data-centric systems; Strong knowledge of: RDF, RDFS, OWL SPARQL Experience with: Knowledge graphs or semantic interoperability platforms; Data modelling and ontology design; Comfortable working with structured data formats: TTL, XML, JSON, CSV Ability to analyse existing models and understand implicit domain logic. Nice-to-Have: Experience with triplestores or graph databases; Familiarity with EU data standards or interoperability frameworks; Python scripting for data processing and/or Apache Airflow; Experience in projects with regulatory or standards-driven constraints. Benefits We believe in rewarding talent and dedication. Here's what you can expect as part of our team: Competitive full-time salary; Private Health Coverage on the Company’s group program; Flexible Working Hours; Top-of-the-Line Tools; Professional Development: Benefit from language courses, specialized training, and continuous learning opportunities; Career Growth: Work with some of the most innovative and exciting specialists in the industry; Dynamic Work Environment: Thrive in a setting that offers challenging goals, autonomy, and mentoring, fostering both personal and company growth. If you want an exciting challenge, work with some of the coolest technologies, and enjoy your time doing it, then join us! Submit your detailed CV in English, quoting reference: ( S/KGE/10/26 ). You may also consider all our other open vacancies by visiting the career section of our website ( www.eurodyn.com ) and follow us on Twitter (@EURODYN_Careers) and LinkedIn. EUROPEAN DYNAMICS (ED) ( www.eurodyn.com ) is a leading European Software, Information, and Communication Technologies company, operating internationally (Athens, Brussels, Luxembourg, Copenhagen, Berlin, Stockholm, London, Nicosia, Valetta, Vienna, Den Haag, Hong Kong, etc.) The company employs over 1200 engineers, IT experts, and consultants (around 3% PhD, 41% MSc, and 54% BSc). We design and develop software applications using integrated, state-of-the-art technology. Our current IT projects have a value exceeding 300 million EURO. EUROPEAN DYNAMICS is a renowned supplier of IT services to European Union Institutions, international organizations, European Agencies, and national government Administrations in 40 countries and 4 continents. As part of our dedication to the diversity of our workforce, we are committed to Equal Employment Opportunity without regard for race, colour, national origin, ethnicity, gender, disability, sexual orientation, gender identity, or religion. EUROPEAN DYNAMICS (ED) adheres to the General Data Protection Regulation principles by applying its Privacy Policy as published at www.eurodyn.com/privacy . By submitting an application to this position and by sharing your personal data with ED, you acknowledge and accept its Policy and authorize ED to process your personal data for the purposes of the company's recruitment opportunities, in line with the Policy.

Location: Abu Dhabi, United Arab Emirates Workplace: hybrid Autonomous vehicles are coming to the markets in which inDrive serves, but the AV industry has a blind spot: it has almost no data from the cities where we operate. inDrive runs one of the world's largest ride-hailing fleets, concentrated in exactly the emerging markets global AV players have yet to reach. We are building the team that turns that fleet into an AV grade data platform: large scale multi sensor collection from real vehicles on real trips, evaluation of driving models against human drivers, automated and human in the loop causal annotation, and camera first 3D scene reconstruction for simulation. We are hiring the founding leader of this workstream. This is a rare true zero to one: you will hire the team, stand up the vehicles and the data platform, set the technical bar, and own delivery end to end. Key Responsibilities Own the AV data workstream end to end. Roadmap, execution, quality, and outcomes, from vehicle data capture through processing, annotation, and delivery of AV-grade datasets Build the team from zero. Hire and lead a multi disciplinary team covering large scale data engineering, search and serving, ML engineering across divergence detection, edge inference, and VLM based auto labeling, 3D reconstruction research, and data annotation operations. Own the hiring bar and the team's growth Management : Manage ML engineers' charter across the cluster Set technical direction across disciplines. Provide design authority for the full pipeline, including onboard capture, cloud ingestion and processing at fleet scale, semantic and causal labeling, and neural scene reconstruction, and make the key technical decisions on evidence Partner with leaders across the organization. Work closely with the leaders of data platform, ML ops, geo and mapping, and inDrive's wider autonomous vehicle initiatives to align roadmaps, share infrastructure, and unblock delivery Own external partnerships. Drive the technical relationships this work depends on, including the NVIDIA AV ecosystem and prospective AV partners consuming our data Balance research and delivery. Several of the core questions here are open research. You frame milestones as decision gates, redirect work based on evidence, and keep the team shipping measurable results on a schedule Skills, Knowledge and Expertise 10+ years of engineering experience in applied ML, autonomous systems, or large-scale data and ML platforms, including 3+ years in the autonomous vehicle industry or closely adjacent autonomy domains (AV data, simulation, or evaluation platforms, ADAS, robotics perception, HD mapping), and 4+ years managing engineering teams, with a track record of building teams from scratch and delivering from zero to one Strong command of the modern AV and foundation model landscape: vision-language models, multi-modal perception, 3D reconstruction and neural rendering, and the NVIDIA AV ecosystem. Deep enough to set direction, review designs, and make evidence-based technical calls Genuine engineering leadership range: you have successfully led data engineering, platform, or infrastructure delivery, not only ML research, and can evaluate and unblock work across those disciplines Proven ability to take large-scale ML systems from conception to production: data pipelines, training and evaluation infrastructure, and models running under real-world constraints Strong external presence: experience owning technical partnerships, vendor and licensing relationships, or customer-facing technical engagements at a senior level Deep fluency in the modern ML stack (PyTorch or equivalent, large-scale training and inference, Python and Linux) and in cloud data platforms at multi-terabyte scale Bachelor's degree in Computer Science, Engineering, or a related field Nice to have: AV industry experience specifically in offline evaluation, data mining, annotation platforms, or simulation, as distinct from on-vehicle stack development Advanced degree (MS or PhD) in ML, robotics, or computer vision Experience operating in emerging markets, and comfort building where the playbook does not exist yet Why join us Help us challenge injustice by creating fair choices for millions of people across 47 countries Develop your professional skills with access to mentoring, career consulting, and learning programs. Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects Work alongside people who take initiative, speak openly, and challenge themselves to grow Improve your language skills through co-financed courses and internal speaking clubs Final benefits may vary depending on the location.

Location: Belgrade, Remote Workplace: remote Tabby creates financial freedom in the way people shop, earn and save by reshaping their relationship with money. Over 25 million users choose Tabby to stay in control of their spending and make the most out of their money. The company’s flagship offering allows shoppers to split their payments online and in-store with no interest or fees. Over 70,000 global brands and small businesses, including Amazon, Noon, IKEA, and SHEIN use Tabby to accelerate growth and gain loyal customers by offering easy and flexible payments online and in stores. Tabby generates over $18 billion in annual transaction volume for its partner brands and is the highest-rated, most-reviewed, largest, and fastest-growing FinTech in the GCC region. Tabby launched in 2019 and has since raised +$1 billion in equity and debt funding from global and regional investors, and is now valued at $6,5 billion. About the role As the Senior Marketing Analyst for CRM, you will be the single analytics owner of CRM - the person marketers come to as a partner. You will own how campaigns are measured, how the communication data is built and trusted, and how insights turn into decisions: what to stop, scale, or fix. You will work closely with CRM marketers, Product, and the data platform team. You define what data you need and accept its quality; you do not build the pipelines yourself. What you will be doing Be the analytics partner to CRM marketers and Product on every initiative. Work with them on how to improve results. Answer "how do we correctly measure CRM activity" questions: choosing the right measurement design for a campaign type (always-on journeys vs one-off blasts vs product launches), defining what "delivered" means per channel, and defending the methodology to stakeholders Explain the technical side in plain language: how an experiment works, what a holdout is for, why a number can or cannot be trusted, so marketers make decisions they actually understand Own how CRM performance is measured: control groups, holdouts, A/B tests Own the CRM analytics data in dbt on BigQuery: who gets which message, on which channel, for which product, and how often Be the customer of the data platform team: say what data you need from the CRM and attribution tools, agree on timelines, and sign off on quality. You own what the numbers mean; they build the pipelines. Build Tableau dashboards that earn their place: visualisations stakeholders can open to check a hypothesis, answer their own question, or spot an insight in minutes. Keep the self-serve AI analytics assistant up to date, so non-technical colleagues can get answers to simple questions and run their own ad-hoc analysis without waiting for an analyst Work with a data science team, ask the right questions about a recommendation or propensity model, spot when it is not doing its job, and drive the test that proves it What you will need 3+ years of experience as a data/marketing/CRM analyst, with exposure to CRM, lifecycle, or retention analytics Strong SQL and hands-on dbt experience (we run dbt on BigQuery); experience designing and maintaining data models, not just querying Experience with CRM engagement platforms: Customer.io , MoEngage, Braze, Iterable or similar: you understand journeys, events, profile attributes, and delivery semantics Solid experience with marketing experimentation: holdout design, global static control groups, control group integrity, A/B tests, incrementality vs attribution Proficiency in Python Proficiency in Tableau (or similar BI tool) Proactive ownership: you find problems in data and processes before stakeholders do, audit your domain independently, and bring your own agenda and ideas on how to achieve business goals. Thinking partnership: stakeholders should be able to brainstorm with you, not just hand you tasks. First-time-right quality: numbers you ship are trusted without a second verification pass; Nice-to-have You now how Uplift modeling and causal ML works and can create MVP version Propensity / churn / LTV modeling Benefits: Locations We hire candidates based within four hours of Dubai time , with remote work available in eligible locations. Depending on your circumstances, we can also discuss an individual relocation plan to our hubs in Armenia, Georgia, Serbia, Poland, and Spain. What you can expect Flexible working hours, coordinated with your team and the needs of your role. Autonomy and responsibility from day one. Opportunities to grow through the quality and impact of your work. Participation in our employee stock option program. We’re committed to an inclusive, high-performing workplace where people from different backgrounds have the support to grow and achieve their goals. If this sounds like the right opportunity for you, we’d love to hear from you.

Location: Poland; United Kingdom Workplace: Remote ABOUT ELEVENLABS ElevenLabs is an AI research and product company transforming how we interact with technology. We launched in January 2023 with the first human-like AI voice model. Today, we serve millions of users and thousands of businesses - from fast-growing startups to large enterprises like Deutsche Telekom and Meta. Our investors are some of the world's most prominent, including Andreessen Horowitz, ICONIQ Growth and Sequoia. We've raised $781M in funding and our last valuation was $22B - multiples of 11, always. We have expanded from voice into three main platforms: - ElevenAgents enables businesses to deliver seamless and intelligent customer experiences, with the integrations, testing, monitoring, and reliability necessary to deploy voice and chat agents at scale. - ElevenCreative empowers creators and marketers to generate and edit speech, music, image, and video across 70+ languages. - ElevenAPI gives developers access to our leading AI audio foundational models. Everything we do is the result of the creativity and commitment of our team - builders doing the best work of their lives. We are researchers, engineers, and operators. IOI medalists and ex-founders. If you want to work hard and create lasting positive impact, we want to hear from you. HOW WE WORK - High-velocity: Rapid experimentation, lean autonomous teams, and minimal bureaucracy. - Impact not job titles: We don’t have job titles. Instead, it’s about the impact you have. No task is above or beneath you. - AI first: We use AI to move faster with higher-quality results. We do this across the whole company—from engineering to growth to operations. - Excellence everywhere: Everything we do should match the quality of our AI models. - Global team: We prioritize your talent, not your location. WHAT WE OFFER - Innovative culture: You’ll be part of a generational opportunity to define the trajectory of AI, surrounded by a team pushing the boundaries of what’s possible. - Growth paths: Joining ElevenLabs means joining a dynamic team with countless opportunities to drive impact - beyond your immediate role and responsibilities. - Learning & development: ElevenLabs proactively supports professional development through an annual discretionary stipend. - Social travel: We also provide an annual discretionary stipend to meet up with colleagues each year, however you choose. - Annual company offsite: Each year, we bring the entire team together in a new location - past offsites have included Croatia and Italy. - Co-working: If you’re not located near one of our main hubs, we offer a monthly co-working stipend. About the role We're looking for an experienced Analytics Engineer to join our Data team as one of its first hires. You will own the transformation layer between raw data and business decisions: modelling our data in dbt, defining the certified metrics the company runs on, and setting the standards that every analyst and data scientist at ElevenLabs builds. - Drive the implementation of a world-class metric layer for the company: modelling conventions, project structure, testing, CI, and documentation. - Design and maintain the certified KPI layer for product (activation, adoption, retention, usage), finance (billing, ARR, revenue), and company-wide topics, built to withstand audit scrutiny. - Partner with Data Engineering on evolving the data warehouse architecture, and with stakeholders to turn ambiguous questions into trusted, reusable data products, including data served through AI agents. Requirements Demonstrated experience building and scaling a dbt project and metrics layer, ideally as one of the first analytics engineers on a growing team. - Expert knowledge of dbt and advanced SQL (required); strong grasp of dimensional modelling, grain, and incremental patterns. - Proficiency across the modern data stack (BigQuery or similar warehouse, Python, BI tools such as Looker). - Rigour around data quality: you test, document, and reconcile by default, and you spot a model that runs cleanly but is quietly wrong. - Strong ability to understand varied stakeholder requirements, push back where needed, and translate them into generalised, well-documented models. Bonus: - Experience modelling billing, subscription and ARR data (Stripe, Salesforce) or product event data at scale. - Experience serving data to LLM-based agents or building semantic / metrics layers consumed by AI tools. - Experience with CI for data (Slim CI, data contracts, PII policy tags) and infrastructure-as-code for warehouse access.   LOCATION This role is remote-first, so it can be executed from anywhere in Europe, with the ability to operate in GMT and GMT+1 timezones. If you prefer, you can work from our offices in London and Warsaw.   #LI-Remote We are an equal opportunity employer and do not discriminate on the basis of race, religion, national origin, gender, sexual orientation, age, veteran status, disability or other legally protected statuses.

Location: Remote, Global 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. More than 9 million developers and 250,000+ customers now build on Supabase, and the majority of new databases on the platform are created by AI app builders — so the systems underneath have to stay reliable while they grow fast. ABOUT THE ROLE Container Engineering (ConEng) owns the internal container platform that runs Supabase's multi-tenant, multi-region services — the managed Kubernetes platform that other engineering teams build and deploy on top of. We own cluster lifecycle and cluster classes, multi-cluster and multi-region topology, capacity, scheduling, isolation and runtime safety, the higher-level platform APIs, the Kubernetes deployment contract and Argo semantics, rollout primitives, and runtime configuration and secret injection.   Your job is to make the platform itself trustworthy, observable, and cheap to operate at scale — and to raise the reliability bar for everyone who depends on it. This is not a gatekeeper role. You'll make the reliable path the easy path: building the automation and platform APIs that let product teams run safely by default, instrumenting what we operate, and making sure that when something breaks we detect it and recover fast.   The work spans three strength areas: Tooling & ecosystem — deep knowledge of the container and orchestration landscape (Kubernetes, containerd/OCI, the CNCF ecosystem) and a clear point of view on how to compose it. Software engineering — designing and building the platform's automation, controllers, and internal tooling as production code, including solutions that don't come pre-shaped by an existing tool. Operational / SRE practice — the discipline (SLOs, error budgets, incident response, ORRs) that runs the platform at scale as a predictable one. We expect you to be genuinely deep in at least one of these, and many of our strongest candidates are deep in two (usually leaning toward one). Bringing real strength across all three is rare and exceptional — and even then, no one is equally strong in all three at once, so you'd focus where you're most needed at any given time. Different profiles are welcome here; tell us which of these is your center of gravity. WHAT YOU'LL BE RESPONSIBLE FOR Regardless of the skill set, all team members carry a share of the team's on-call rota, responding to platform incidents and driving them to resolution and follow-up. Platform reliability & operations - Define SLIs/SLOs and error budgets for the container platform itself, and build error-budget policies that actually gate platform changes. - Own the Operational Readiness Review (ORR) process for new platform capabilities and major changes. - Design and track metrics for platform uptime, and increase observability into the platform by capturing the right metrics, logs, and traces across the platform layers. - Drive the incident-to-improvement pipeline: facilitate blameless postmortems, connect findings to readiness gaps, spot repeat failure patterns, and push through systemic fixes. Software engineering - Build and maintain the platform's automation, controllers, operators, and internal tooling — writing production code and shipping it, not just wiring together existing tools. - Design and implement the platform-side CI/CD and rollout primitives that speed up platform deployments while working within proper change and release management. - Implement and maintain security automation for the platform: intrusion detection, automated remediation, and patch management. - Identify and quantify operational toil, and build the automation that removes it rather than just documenting it. - Contribute to the platform's continual testing automation — the test suites and pipelines that validate platform releases are fit for purpose before they reach tenants. Tooling, ecosystem & architecture - Act as a platform reliability and architecture expert — contribute to failure-mode analysis, dependency mapping, and resilience design for multi-tenant container workloads. - Evaluate and evolve the platform's tooling ecosystem (orchestration, runtime, networking, isolation, and observability stack) with a clear, opinionated view on trade-offs. - Improve system architecture to reduce infrastructure cost while balancing security, reliability, and performance across tenants. - Guide teams building on the platform to design sustainable on-call practices for their own services: alert quality, escalation paths, runbook coverage, and noise reduction.   YOU MIGHT BE A GOOD FIT IF YOU - Have 5+ years in platform engineering, container/Kubernetes platform operations, SRE, or production infrastructure, and have operated production systems at scale and carried on-call for them. - Are genuinely deep in at least one — ideally two — of the three strength areas below (and tell us which is your center of gravity): - Tooling & ecosystem — know the container/orchestration landscape well: Kubernetes, containerd and the OCI/CRI standards, and the surrounding CNCF ecosystem (e.g. Argo CD/Argo Rollouts for GitOps and progressive delivery; Cilium/eBPF networking and the Gateway API; Karpenter/KEDA-style autoscaling; and workload-isolation runtimes such as gVisor or Kata Containers). You reason about trade-offs rather than reaching for defaults. - Software engineering — write real production code (Go and/or a comparable systems language) and can build controllers, operators, and platform APIs — stepping back to the underlying problem and building the right solution when no off-the-shelf tool fits. - Operational / SRE practice — are fluent in SLOs, error budgets, and operational KPIs; have led incident response and blameless postmortems; and have driven down MTTD/MTTR for systems you operated. - Have worked with large-scale multi-tenant systems and understand isolation as a spectrum — from namespaces, RBAC, network policies, and resource quotas through to stronger primitives such as virtual clusters (e.g. vCluster) or VM-class runtimes. - Operate confidently on AWS (multiple accounts, IAM, VPC) and are comfortable with infrastructure-as-code (Pulumi preferred; Terraform/CDK also fine) and Kubernetes. - Script and automate to eliminate toil rather than absorb it. - Communicate clearly with both infrastructure specialists and product engineers, and thrive in async, globally distributed teams. - Are comfortable navigating ambiguity and iterating toward better systems over time. Nice to Have - Experience building and operating a multi-tenant Kubernetes platform that internal teams deploy onto. - Familiarity with policy engines (Kyverno, or OPA/Gatekeeper) and cost-attribution tooling (OpenCost/Kubecost) for per-tenant chargeback/showback. - Experience with managed database platforms or Postgres. - Familiarity with OpenTelemetry, Prometheus/VictoriaMetrics, Grafana, or similar observability tooling. 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.

Location: Athens, Greece We are seeking a Semantic / Data Engineer to support a complex platform built around RDF data models, SPARQL queries, and structured datasets. You will be responsible for understanding, maintaining, and evolving the semantic layer of the system, working closely with backend engineers and architects. This role suits a specialist who enjoys data modelling, semantics, and knowledge representation in real-world production systems. What You'll Do: Analyse and maintain RDF/TTL data models and vocabularies; Develop, optimise, and maintain SPARQL queries; Support data ingestion, transformation, and validation workflows; Ensure consistency and correctness of semantic data across the platform; Collaborate with backend engineers to integrate semantic logic into application flows; Assist in documenting semantic models, assumptions, and constraints; Participate in troubleshooting data quality and reasoning issues. Requirements 3+ years of experience working with semantic or data-centric systems; Strong knowledge of: RDF, RDFS, OWL SPARQL Experience with: Knowledge graphs or semantic interoperability platforms; Data modelling and ontology design; Comfortable working with structured data formats: TTL, XML, JSON, CSV Ability to analyse existing models and understand implicit domain logic. Nice-to-Have: Experience with triplestores or graph databases; Familiarity with EU data standards or interoperability frameworks; Python scripting for data processing and/or Apache Airflow; Experience in projects with regulatory or standards-driven constraints. Benefits We believe in rewarding talent and dedication. Here's what you can expect as part of our team: Competitive full-time salary; Private Health Coverage on the Company’s group program; Flexible Working Hours; Top-of-the-Line Tools; Professional Development: Benefit from language courses, specialized training, and continuous learning opportunities; Career Growth: Work with some of the most innovative and exciting specialists in the industry; Dynamic Work Environment: Thrive in a setting that offers challenging goals, autonomy, and mentoring, fostering both personal and company growth. If you want an exciting challenge, work with some of the coolest technologies, and enjoy your time doing it, then join us! Submit your detailed CV in English, quoting reference: ( SDE/10/26 ). You may also consider all our other open vacancies by visiting the career section of our website ( www.eurodyn.com ) and follow us on Twitter (@EURODYN_Careers) and LinkedIn. EUROPEAN DYNAMICS (ED) ( www.eurodyn.com ) is a leading European Software, Information, and Communication Technologies company, operating internationally (Athens, Brussels, Luxembourg, Copenhagen, Berlin, Stockholm, London, Nicosia, Valetta, Vienna, Den Haag, Hong Kong, etc.) The company employs over 1200 engineers, IT experts, and consultants (around 3% PhD, 41% MSc, and 54% BSc). We design and develop software applications using integrated, state-of-the-art technology. Our current IT projects have a value exceeding 300 million EURO. EUROPEAN DYNAMICS is a renowned supplier of IT services to European Union Institutions, international organizations, European Agencies, and national government Administrations in 40 countries and 4 continents. As part of our dedication to the diversity of our workforce, we are committed to Equal Employment Opportunity without regard for race, colour, national origin, ethnicity, gender, disability, sexual orientation, gender identity, or religion. EUROPEAN DYNAMICS (ED) adheres to the General Data Protection Regulation principles by applying its Privacy Policy as published at www.eurodyn.com/privacy . By submitting an application to this position and by sharing your personal data with ED, you acknowledge and accept its Policy and authorize ED to process your personal data for the purposes of the company's recruitment opportunities, in line with the Policy.

Location: Europe or US Workplace: Remote About the team The Control Plane Platform team is building the shared foundation that every product in ClickHouse Cloud is built and shipped on. We give ClickHouse engineering teams one place to own and deploy their product, remove the overhead of rebuilding common plumbing, and keep the customer experience consistent as the number of integrating teams grows. The team owns API gateways and API standards, shared platform services, deployment and infrastructure patterns, testing and CI, local developer experience and Control Plane observability. About the role We’re looking for an Engineering Manager to lead our Platform team. This is a high-impact, high-trust role at the center of our Cloud product, combining people leadership, technical direction, product thinking, and operational ownership while maintaining the reliability customers expect. You’ll work hand-in-hand with Product, Infrastructure, Security, Support, and engineering teams across ClickHouse. This role goes beyond engineering leadership. Together with your team, you’ll help shape how new products and teams will integrate and deploy their applications in ClickHouse Cloud. What You’ll Do - Lead, coach, and grow a high-performing team - recruit to a high bar, set crisp expectations, give direct feedback and career development, and manage performance — while fostering a healthy, inclusive environment built on empathy, psychological safety, trust, and a high technical bar. - Own outcomes across the platform surface: API gateways and API standards, shared platform services (event bus, notifications, feature flags, websockets, audit records), deployment and infrastructure patterns, CI and testing, local developer experience, disaster recovery, and Control Plane observability. - Treat the integrating teams as your customers and measure success by their delivery velocity and adoption of the platform, not only by what your team ships. - Guide architecture and help senior engineers make explicit, sound tradeoffs. land cross-cutting migrations, deprecations, and contract changes across teams without stalling product delivery. - Jump into designs and code for complex areas - gateway routing and auth/RBAC enforcement, spec-driven code generation, event delivery semantics and idempotency, multi-region rollout safety. - Build the culture of operational excellence: Own SLOs, reliability, on-call quality, and cost-efficiency for k8s-hosted, multi-tenant services across cloud regions. - Systematize support, reduce toil, and build self-serve/auto-healing capabilities - golden-path templates and generators, auto-healing, and documentation that gets a new team integrated in days rather than weeks. - Shape the platform vision, turn it into a roadmap, sequence bets for business impact, and ship fast with tight feedback loops — including writing the RFCs that build cross-org consensus before big changes land What you bring - 8+ years in software engineering and 3+ years managing software engineers with a track record of hiring, developing, and retaining strong talent. - Experience leading a platform or infrastructure team whose customers are other engineering teams — you've driven adoption and cross-org migrations through influence and good tooling rather than mandate. - Experience leading distributed global teams, fostering an inclusive and autonomous culture, and creating clarity across time zones. - Experience building scalable, highly available, and secure cloud-based infrastructure in AWS (EKS, SQS, DocumentDB, Redis, PostgreSQL, Lambdas) with infrastructure as code (Terraform, Helm) and progressive delivery (Argo Rollouts or similar). - Experience with containerization and orchestration (Docker, Kubernetes), including patterns for hosting many independently deployed applications in a shared cluster. - Familiarity with API platform work: OpenAPI-driven contracts, API gateways, and the shared concerns they centralize — authentication, RBAC, rate limiting, versioning, and deprecation. - A track record of decomposing a monolith into independently deployable services without stalling product delivery. - Technical credibility to engage deeply in architecture and incidents without owning daily implementation. - Hands-on: you still enjoy diving into code/designs for complex or critical areas, reviewing code, and guiding via feedback. - Strong execution judgment across ambiguity, parallel workstreams, risk, and long-term system health. Nice to have - Experience with large TypeScript/Node monorepos and the developer-experience problems that come with them: CI scale and flakiness, build and test times, local development environments, and code generation from specs. - Designed and implemented strategies for load balancing, auto-scaling, disaster recovery, and failover for cloud environments. - Experience building CI/CD at scale - Experience with internal developer platforms: service catalogs, golden-path templates, and self-service app scaffolding. - Proficiency with frontend frameworks (React). - Experience making APIs consumable by AI agents — MCP servers, CLIs, or skills generated from API specs. - Experience with ClickHouse - Previous experience in developing analytics or data-intensive applications. Why This Role - Shape how all feature teams in ClickHouse Cloud develop and integrate with each other - Operate with ownership, autonomy, and speed while keeping the company lean. - Lead a technical team where correctness, performance, reliability, and developer experience all matter. PERKS - Flexible work environment - ClickHouse is a globally distributed company and remote-friendly. We currently operate in over 25 countries. - Healthcare - Employer contributions towards your healthcare. - Equity in the company - Every new team member who joins our company receives stock options. - Time off - Flexible time off in the US, generous entitlement in other countries. - A USD$500 Home office setup if you’re a remote employee. - Global Gatherings – We believe in the power of in-person connection and offer opportunities to engage with colleagues at company-wide offsites. CULTURE - WE ALL SHAPE IT As part of a rapidly scaling start-up, you will be instrumental in shaping our culture. Are you interested in finding out more about our culture? Learn more about our values here https://clickhouse.com/company/careers. Check out our blog posts https://clickhouse.com/blog or follow us on LinkedIn https://www.linkedin.com/company/clickhouseinc/life/0c1ee7f4-2129-488d-b413-e7f6270659fd/?viewAsMember=true to find out more about what’s happening at ClickHouse. EQUAL OPPORTUNITY & PRIVACY ClickHouse provides equal employment opportunities to all employees and applicants and prohibits discrimination and harassment of any type based on factors such as race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Please see here https://clickhouse.com/legal/applicant-privacy-notice for our Privacy Statement.

Location: San Francisco Perplexity is AI for people who expect more. This role brings that same standard to how our data team works, with AI at the center of everything we do. We're looking for someone who's been a great data scientist, analytics engineer, or data engineer: the kind of person who knows which metric actually matters, can design an A/B test that answers the real question, has gone deep on a data model because something didn't add up, and has decided that the highest-leverage thing they can do next is build AI systems that fundamentally change how data science gets done. You'll build AI agents and internal systems that can increasingly handle end-to-end analysis workflows: forming hypotheses, writing and running queries, interpreting results, and drafting recommendations with the right evaluation, review, and guardrails. You'll build the retrieval infrastructure and evaluation loops that let AI systems query the warehouse reliably. You'll create workflows that detect, diagnose, and help fix data issues before they become company-wide problems. You'll build the infrastructure that multiplies what a small data team can ship. You'll join a data team that's already using AI across its work. The next step is turning those individual workflows into scalable systems, shared tools, and an AI-native operating model that becomes a benchmark for how modern data teams work.   WHAT YOU'LL DO - Build AI agents that do data science - not just SQL copilots, but systems that can safely explore data, form hypotheses, run queries, interpret results, and generate actionable recommendations with clear evaluation and human review loops. - Make AI systems query the warehouse reliably - build the retrieval infrastructure and evaluation loops that let agents use our semantic context and metadata accurately. - Accelerate the AI-native data workflow - turn the best existing AI-assisted workflows into repeatable systems, reusable tools, and patterns the whole data team can adopt. - Automate the data lifecycle - build self-healing pipelines, automated dbt model generation and validation, data quality agents, and diagnosis workflows that reduce manual firefighting. - Ship AI-powered experiment analysis - build agents that interpret A/B test results, flag statistical issues, identify likely drivers, and draft ship/no-ship recommendations. - Turn the data team into a product team - build internal data products that stakeholders use every day, replacing ad hoc requests with self-serve AI interfaces. - Own the full lifecycle - identify high-leverage problems, prototype with LLMs, evaluate accuracy, design the UX, ship to production, and monitor quality over time. WHAT WE'RE LOOKING FOR - 6+ years in data science, analytics engineering, data engineering, or a related role. You've been close enough to real data work to know what should and should not be automated. - Deep SQL and analytics judgment - you can reason through metrics, experiments, data models, and messy warehouse reality without relying on a tool to think for you. - Strong product sense - you understand what stakeholders actually need, what makes a workflow adoptable, and how to turn a prototype into a product people use. - Hands-on LLM experience - you've built with frontier models, agents, RAG systems, evals, or AI-powered workflows and have opinions about where they work and where they fail. - Pipeline and modeling fluency - you've worked with dbt, warehouse schemas, data quality issues, and the practical tradeoffs behind durable data systems. - Builder mentality - you see a manual process and immediately think about how to systematize it. You ship fast, measure quality, and iterate. - Autonomy - this is a new function. You'll help define the roadmap as much as execute it. BONUS - Experience building production AI agents or agent evaluation systems. - Experience with Snowflake, semantic layers, or metadata systems. - Experience building internal tools, Slack bots, CLIs, or developer productivity products that people actually used. - Strong experimentation background, including metric design and statistical interpretation. - Experience with BI tools and the judgment to know what should be automated versus kept human-reviewed. - Early-stage startup experience. WHY THIS ROLE - Set the standard for the industry - Perplexity's data team is already using AI across its work. You'll turn that into something other data teams look to as the benchmark. - Build AI with AI - Perplexity builds AI for people who expect more. You'll bring that same level of ambition to how the company works with data. - Frontier models, day one - you're at an AI company with access to frontier infrastructure and people who deeply understand what's possible. - Massive leverage - the systems you build will multiply the output of every data team member and every stakeholder who needs data. - Direct impact - small team, no layers of approval. Idea to shipped system in days, not quarters.

Location: San Francisco, CA; Sunnyvale, CA Workplace: Hybrid ABOUT NIANTIC SPATIAL AI has learned from almost everything online, but it still struggles with the physical world, where 99.5% of economic activity happens. It doesn’t know where things are, how spaces fit together, or what changes over time. That’s one of the biggest unsolved problems in AI, and it’s the one we’re solving at Niantic Spatial. We build spatial AI models and services so people and machines can reason, learn and act safely in the physical world. We turn camera imagery, video, sensor data and archives into accurate, AI-readable representations of real places that robots can train in and machines can use to know exactly where they are. In physical AI, mistakes have real consequences. That’s why we build AI grounded in measured reality, not guesswork, so the people and machines relying on it can trust it to get things right. Our team built some of the world’s most widely used maps. Now we’re building something bigger: a living, measured record of the real world that machines can query, learn from and use to understand how places change over time. If you want to help AI understand the world we actually live in, come build with us. THE OPPORTUNITY As a staff member of the Map Team, you’ll own and drive significant parts of our Reconstruction and/or Localization technologies. You will be responsible for building the Map representing a living geospatial world model that can be simultaneously used to generate a high-fidelity 3D representations via Gaussian Splatting and Meshing, as well as the centimeter-level accuracy Visual Positioning System (VPS) that allows people and robots to explore the real world. This is an individual contributor role with a strong component of technical leadership where you will mentor other engineers and influence the technical roadmap. WHAT YOU WILL DO - Technical Leadership: Lead the design and implementation of some of our core technologies, namely, Structure from Motion (SfM), Feed Forward and Foundational models, and high-fidelity 3D Reconstruction (e.g. meshing, gaussian splats). - Applied Research: Up to speed state-of-the-art in relevant areas to be able to invent novel solutions in VPS and/or 3D Reconstruction alongside the team. - System Architecture: Design, develop, and maintain scalable production-grade Computer Vision systems that power Niantic Spatial’s VPS, 3D Reconstruction and 3D Mapping pipelines. - Algorithm optimization and production implementation: develop and optimize algorithms, train models, for high-accuracy and high-performance execution on CPU/GPU on the cloud or device as part of a reliable production system. - Quality & Benchmarking: Drive decision-making creating high quality data that allows the accurate spatial grounding of AI queries with structural, semantic and location specific knowledge. - Technical Strategy & Mentorship: Work with engineering leadership to define the technical roadmap and quarterly objectives for the Applied CV Team; provide high-level mentorship and code governance to elevate the team’s technical bar. - Cross-Functional Delivery: Collaborate with Product, Research, and Operations teams to ensure that state-of-the-art Computer Vision solutions translate into delightful user experiences. WHAT WE ARE LOOKING FOR - Years of Experience: 7+ years of professional experience in Computer Vision, Machine Learning, or a related field (or 4+ years with a PhD in a relevant domain). - Education: Bachelor’s degree in Computer Science, Engineering, or a related technical field; Master's or PhD preferred. - Core Technical Skills: Strong proficiency in Python and/or C/C++. - Specialized Expertise: Proven experience in both classical and learned-based 3D Computer Vision and ML. - Full SW lifecycle experience: Demonstrated experience in taking research into production at scale. - Technical Leadership Experience: Previous experience tech leading computer vision projects. COMPENSATION & BENEFITS The expected salary range for this role is $256,500 – $315,000 per year. Compensation also includes an annual bonus, equity, and a comprehensive benefits package including medical, dental, and vision coverage, 401(k), and more. LOCATION & WORK MODEL This role is based in our San Francisco or Sunnyvale office, with three days per week in office. INCLUSIVE APPLICATION We know the strongest candidates don't always tick every box. If you're excited about this role and believe you could do it well, we encourage you to apply even if your experience doesn't match every qualification listed — you may be exactly who we're looking for. EQUAL OPPORTUNITY Niantic Spatial is an equal opportunity employer. Individuals seeking employment at Niantic Spatial are considered without regard to race, color, ancestry, national origin, religion, creed, age, gender (including pregnancy, childbirth, breastfeeding or related medical conditions), marital status, physical or mental disability, medical condition, genetic information, military or veteran status, gender identity, gender expression, sexual orientation, or any other protected category under applicable laws. Niantic Spatial will also consider qualified applicants with criminal histories in accordance with applicable laws. Please contact your recruiter if you want to request an accommodation for the job application or interview process. CANDIDATE PRIVACY I understand that by submitting my job application, the information I provide as part of that application will be used in accordance with Niantic Spatial's Privacy Notice for Job Applicants and Candidates https://www.nianticspatial.com/applicant-privacy-notice.

Location: Remote - Australia Workplace: Remote Qdrant is an open-source vector search engine powering the next generation of AI applications, from semantic search and retrieval-augmented generation (RAG) to AI agents and real-time recommendations. Trusted by global leaders like Canva, HubSpot, Tripadvisor, Bosch, and Deutsche Telekom, we’re building the retrieval infrastructure layer for modern AI. Recently raising $50M in Series B funding, we are growing rapidly and committed to transforming how AI understands and interacts with data. As a remote-first company, we believe diverse backgrounds, perspectives, and experiences fuel innovation. Here, you’ll own meaningful work, tackle challenges, and grow alongside passionate individuals dedicated to shaping the future of AI. You'll join the Customer Success and Engineering organization as our first Senior Technical Success Manager hire in Australia or Japan, reporting to our Director of Customer Success. Our Technical Success Managers in the US and Europe own the post-sale relationship for our most strategic accounts. In APAC, you'll do that and more: you'll be the technical face of Qdrant in the region, working with Account Executives, Support, Forward Deployed Engineers, and Solutions Architects who sit several time zones away. Most of your time goes to helping customers who already run Qdrant in production succeed and grow. The rest goes to supporting new deals, partner work, and first-line technical questions in APAC hours. It's a hybrid role for someone who likes being first in, figuring things out, and building how we work in a new region. What you will own - Strategic APAC accounts, end to end. Be the primary technical owner for our largest customers in the region, from onboarding through production, scaling, and expansion. Run health checks and architecture reviews, and spot growth opportunities before the customer asks. - Hands-on delivery. Work directly with customer engineering teams on deployment, configuration, and performance tuning across Qdrant Cloud and self-hosted Kubernetes environments. - First-line technical support in APAC hours. Resolve most technical questions yourself, and hand edge cases to Support and Engineering with clear, evidence-based diagnostics so nothing stalls overnight. - Expectation setting with demanding customers. Hold the line on scope, priorities, and customization requests, and align engineering, IT, and security stakeholders on what happens next and when. - Pre-sales and partner support. Back Account Executives on new opportunities and proofs of concept in the region, and help regional partners' technical teams position and deploy Qdrant. - The voice of APAC customers. Bring field feedback to Product and Engineering, and help shape the playbooks and processes we'll use as the region grows. Who you are - You have 6+ years in customer-facing technical roles (Technical Account Manager, Technical Success Manager, Solutions Architect, Solutions Engineer, or Forward Deployed Engineer) at an AI, data, or database infrastructure company. - You're hands-on with cloud-native infrastructure: Kubernetes, Terraform, and at least one major cloud (AWS, GCP, or Azure). You can reason about memory, performance, and scaling problems without waiting for someone else. - You've worked both sides of the deal. You can support a technical evaluation as comfortably as you can run a long-term customer relationship. - You bring enterprise maturity. You'll be dealing with our biggest enterprise clients in the region, so you negotiate confidently with engineering, IT, and security teams, and you push back with care when a customer's request doesn't serve them. - You're self-sufficient and enjoy startup ambiguity. You can be the only Qdrant person in your time zone, make good calls on your own, and know when to delegate or escalate. - You're based in APAC, ideally Australia, communicate clearly in English, and can occasionally join early or late calls with teammates in Europe and the US. Nice to have - Direct experience with vector search or search engines, or RAG and agentic AI applications in production. - Experience as an early or first hire building a regional presence for a start-up or scale-up. WHY JOIN US - A remote-first, international team working on cutting-edge AI infrastructure. - A competitive salary with additional perks. - Flexible working hours and async-friendly culture. - High ownership and real impact. - Open-source, engineering-driven culture. - Choose your own laptop equipment. For US-based full-time employees, we also offer a comprehensive benefits package including 401k match, health, dental, and vision insurance, plus flexible PTO policy. Qdrant is an equal-opportunity employer. We believe the best ideas come from diverse teams, and we actively welcome applicants from all backgrounds. If this role excites you but you don't check every single box, we'd still love to hear from you! We don't want to miss out on great people because of a checklist. Come build with us! FOR INFORMATION ON HOW WE HANDLE YOUR PERSONAL DATA, PLEASE REFER TO OUR RECRUITMENT PRIVACY POLICY https://qdrant.tech/legal/recruitment-privacy-policy/ #LI-REMOTE

Location: Toronto; San Francisco; Canada; United States; New York; Ottawa; Montreal Workplace: Hybrid WHO ARE WE? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! WHY THIS ROLE? We’re building the foundational infrastructure that will define how the world thinks about and deploys AI, and we want the sharpest, most driven, and most curious people to help us do it. As the head of the Data Foundation pillar of our Analytics and Data Insights team, you’ll lead the team that makes Cohere’s data trustworthy, governed, and available: the warehouse every analytics surface runs on, the pipelines that keep it fresh, the access model that keeps it secure, and the agentic analytics layer that lets anyone at Cohere (and their agents) ask questions of governed data directly. Your team owns the full data lifecycle. You’ll run ingestion into BigQuery from internal and external data sources, orchestrate it in Airflow and Cloud Run, model the data warehouse in dbt, and serve the results through Looker, export APIs, and customer-facing analytics surfaces. Everything is provisioned as code in Terraform, and governance is part of the design: VPC service controls, IAM patterns, and documented access paths that let people and agents move fast without putting data at risk. This role is both highly visible and highly impactful, and you’ll inherit a solid structure on which to build the rest of the stack: a Terraform-provisioned warehouse framework, dbt modeling conventions, an alerting and incident-response practice, and documentation patterns to keep everything discoverable. The roadmap is set with big bets in flight: scaling that framework across the company, standing up an internal analytics agent with a real eval harness, and consolidating institutional knowledge into a self-correcting and self-maintaining system that keeps context centralized, current, and documented, rather than dispersed and in people’s heads. Responsibilities As the head of the Data Foundation pillar, you will: - Build and lead the team. Hire and grow a team of data and infrastructure engineers; set the technical bar; develop strong talent and raise team performance, building leadership capability beneath you. - Set the roadmap from company strategy. Own and sequence the Data Foundation roadmap: the warehouse buildout, the agentic analytics program, data governance, and the platform work that unblocks our other pillars. You’ll make the trade-offs and carry the cross-functional impact that comes with them. - Own the data platform end to end. Ingestion (managed connectors and an open-source connector framework), orchestration on Airflow and Cloud Run, warehouse modeling in BigQuery with dbt (raw, core, mart layers), and serving through Looker, export APIs, and semantic layers. All of it provisioned as code in Terraform. - Own data governance. Define how humans, service accounts, and agents get access to governed data: VPC service controls, IAM patterns, documented onboarding paths, audit logs, and sensitive requests (including legal holds) handled to deadline. - Operate for reliability. Run the alerting and anomaly-detection framework, own data freshness SLAs, lead incident response and postmortems, and turn every incident into a durable standard so the same class of failure doesn’t recur. - Lead the agentic analytics program. Wire the semantic layer into an internal analytics agent, build the eval harness that measures its accuracy, and make the eval-driven call on where AI earns its way into production. Apply the same discipline to automating data engineering work itself. - Set the standard for analytics across the company. The medallion framework, naming conventions, and testing patterns your team maintains become the way other teams ship analytics data. You’ll onboard new domains onto it and keep the docs accurate to how the systems actually work. - Partner across the org. Work with the North product and engineering teams on the analytics surfaces that ship in the product (including a customer-facing analytics export), with Business Insights on marts for the business, with Security on data governance, and with Legal on compliance-critical data requests. QUALIFICATIONS You may be a good fit, if you have: - 10+ years of experience across data engineering, data infrastructure, or analytics platform work, with a strong management track record leading data platform or infrastructure teams - Serious hands-on history in data engineering or infrastructure before management. You can still read a Terraform plan, a dbt DAG, or an Airflow scheduler log and ask the question that matters - Production experience with cloud data warehouses (BigQuery, Snowflake, or similar), workflow orchestration (Airflow or similar), and infrastructure as code (Terraform or similar) - Depth in data modeling: you think in fact and dimension tables, raw/core/mart separation, and semantic layers, and you have opinions on where tests and contracts belong - A record of setting a team’s roadmap from company or function strategy and delivering outcomes that span teams, with the cross-functional partnerships to match - Operational excellence you can point to: alerting you trust, SLAs you meet, incidents you run to ground and write up so they teach - Exposure to data security and governance: IAM, access management, VPC service controls or equivalent, audit and compliance workflows - Genuine excitement about AI: you follow the research, have opinions, and are energized by building the data foundation an AI company (and its AI agents) runs on - Comfort operating in ambiguity, leading a multi-workstream roadmap, and working directly with executives on priorities If some of the above doesn’t line up perfectly with your experience, we still encourage you to apply! FULL-TIME EMPLOYEES AT COHERE ENJOY THESE PERKS: - A weekly lunch stipend of $75/£75 or equivalent in your local currency for lunch. - Full health and dental benefits, including a separate budget for mental health. - RRSP matching, 401K, Pension Scheme. - 100% Parental Leave top-up for up to 6 months, for either parent. - Annual enrichment benefits: Arts & culture, fitness/wellness, quality time, and a workspace improvement credit. Education & learning stipend for conferences, courses, and coaching. - 6 weeks of paid vacation (30 working days!) - Budget for traveling to other offices if you are remote, plus an annual company offsite. HOW AND WHERE WE WORK: - Cohere is remote-friendly, but we also have offices in Toronto, London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul with more opening soon. - For those in the office: a daily lunch program, plenty of snacks, and regular community and social events. - For those not near an office: a co-working benefit so you can work alongside others in your city. - Everyone receives a $500 home office stipend to set up your workspace properly. If any of the above doesn’t line up exactly with your experience, we still encourage you to apply. We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form https://docs.google.com/forms/d/12a6IrLdF3kI2nonKSr4tiFuz18rLQbaeYV-JM9L4o9Q/edit, and we will work together to meet your needs. We may use AI-enabled tools to screen and assess applicants against the criteria for this position. This helps our recruiters identify potentially qualified candidates, but it doesn't limit the applications our recruiters may review or consider. Beware of Scams: Cohere will never ask for payment or third-party services (e.g., CV writing) as part of our hiring process. All legitimate roles are listed on the Cohere careers page and LinkedIn only, with all communications from Cohere employees coming from an @cohere.com or @cw.cohere email alias. If jobs are viewed on other sites then please verify these through our official careers https://cohere.com/careers page.

Location: Remote About the Team: Netlify’s Data team helps the company understand and improve the full product-led growth journey, from activation and engagement through conversion, retention, and monetization. We partner closely with Product, Engineering, and Growth to uncover opportunities, evaluate investments, and understand what drives customer and business outcomes. We’re hiring a Senior Staff Data Scientist to deepen how data shapes our product and growth strategy. You’ll develop an end-to-end understanding of the PLG journey, proactively identify opportunities, and turn complex data into hypotheses, experiments, and recommendations that influence where we invest and what we build. This is a highly autonomous role for someone who can move from identifying an important question to shaping the approach, defining success, and driving toward an answer. What You'll Do: Own the analytical understanding of Netlify’s PLG performance across activation, engagement, conversion, monetization, and retention, identifying opportunities before they become requests Partner with Product and Engineering leadership to turn behavioral insights into product bets, defining what to test, how to measure it, and what the results mean Lead experimentation from hypothesis through decision, including study design, methodology, success metrics, guardrails, analysis, and recommendations Apply statistical rigor where it matters while recognizing when there is enough signal to make a decision and move forward, and help teams develop that same judgment Build scalable analytical systems like semantic models, trusted metrics, proactive monitoring, and AI-powered agents  that surface opportunities without waiting to be asked Use AI to investigate faster, automate recurring analytical work, and test more hypotheses without sacrificing the judgment that makes the output useful Identify gaps in measurement, event instrumentation, and metric definitions, and partner with Data and Product Engineering to close them Serve as a trusted analytical partner to PLG leadership, using evidence and product judgment to influence investment decisions and roadmap priorities Influence product strategy through evidence, product instincts, and a clear point of view, without relying on formal authority to do it What You'll Bring: 8+ years of experience in product analytics, growth analytics, or data science, with a track record of high ownership and measurable impact on PLG or consumer product outcomes Deep understanding of product and growth dynamics across activation, engagement, conversion, monetization, and retention Demonstrated ability to turn behavioral data into product hypotheses and carry them from insight through experimentation and measured outcomes Deep experimentation expertise: study design, statistical reasoning, causal inference, and the judgment to know when an experiment has told you what you need to know Experience building analytical systems such as metrics layers, monitoring frameworks, or semantic models that teams can rely on over time An AI-native approach to analysis: you use AI tools actively to accelerate investigation, automate repetitive work, and surface patterns faster A track record of influencing senior stakeholders and product direction through analytical reasoning, clear recommendations, and sound judgment Comfort operating with significant autonomy in ambiguous problem spaces, including determining which questions are most important to answer Strong written and verbal communication skills in distributed environments, with the ability to make complex findings clear and recommendations actionable This Role is a Great Fit If: You're energized by finding the opportunity before anyone thought to ask - proactive discovery is how you naturally work, not a mode you shift into You think like a product person who happens to be exceptionally rigorous with data, not a data person who occasionally weighs in on product You thrive when the problem isn't handed to you - you'd rather define the question worth asking than answer the one that landed in your queue You get excited about building systems that keep working after you've moved on to the next problem You're comfortable making a call with imperfect information and can articulate clearly why you made it You enjoy being a thought partner to senior leaders - shaping how they think about investment and opportunity, not just supporting decisions already made You work well in a remote-first, async environment where written clarity and self-direction matter more than proximity You're drawn to roles where the measure of success is outcomes, decisions made, bets tested, metrics moved, not volume of output produced Applying Not sure you meet 100% of our qualifications? Please apply anyway! When applying please include: A resume or short listing of your job history & skills (link to a LinkedIn profile would be fine). We appreciate a cover letter explaining why you would enjoy working in this role at Netlify to get to know you a bit better, though this is not required and will not impact your application. Our mission is to “build a better web” and that cannot be done without a diversity of skill sets, backgrounds and thoughts. Of everything we've ever built at Netlify, we are most proud of our team. Netlify is an Equal Opportunity Employer. We are devoted to building a team of people with diverse backgrounds and lifestyles. Driving equality empowers our team, enables us to innovate, and helps us maintain a more inclusive environment. We don’t discriminate against employees or applicants based on gender identity or expression, sexual orientation, religion, age, race, military/veteran status, citizenship, pregnancy status, or any other differences. If we can do anything to provide a better interview, i.e. accommodate a disability, then please let us know by emailing accommodations@netlify.com . About Netlify Netlify is the most popular way to build, deploy, and scale modern web applications, empowering everyone from fast moving solo developers to enterprise teams. Millions of developers and organizations rely on Netlify as their platform of choice for composing web applications that are production ready, performant, and flexible. Now, as we embrace the next era of software development, we are embedding the same fluid, intuitive experience into the Agent Experience (AX), making it just as simple for intelligent agents to understand, interact with, and act on our platform as it is for developers. Whether your user is human or machine, Netlify ensures the path from idea to URL is seamless, fast, and deeply reliable. We are a Series D company that has raised over $200M from investors such as Andreessen Horowitz, Kleiner Perkins, EQT, Bessemer, BOND, and Menlo Ventures. As a fully distributed company, we aim to create a company culture where the best idea can come from anywhere and strive to be thoughtful, compassionate, and collaborative in our work. If this sounds like something you’d like to be part of, we’re excited to connect with you! At Netlify, we are committed to a compensation philosophy that prioritizes fairness and equity, positions our employee compensation competitively in the market, recognizes and rewards performance, and takes a comprehensive approach to our rewards package. We anchor our compensation philosophy on a market-based approach, therefore salary ranges may differ depending on the labor cost in a particular location. The salary provided is in addition to robust benefits and participation in Netlify’s equity plan. Our hiring range for this role is targeted at $204,000 - $275,000 for most US-based locations.  Candidates outside the US or in premium markets should consult with their Talent Acquisition partner regarding location-based ranges, as they may be higher or lower than the average US range listed. The starting pay will be determined based on multiple factors, including expertise and skills, market demands, experience, internal equity, and applicable geographic location. These compensation packages and ranges are subject to change and may be modified in the future.

Location: Singapore About Cantina: Cantina Labs is a social AI company, developing a suite of advanced real-time models that push the boundaries of expression, personality, and realism. We bring characters to life, transforming how people tell stories, connect, and create. We build and power ecosystems. Cantina, our flagship social AI platform, is just the beginning. About the Role: Cantina is expanding, and we're looking for an ML Engineer to join our growing Singapore team! In this role, you will build and scale systems for ingesting, processing, and delivering large-scale video and multimodal data for model training. You'll own the full pipeline — from raw content to curated, filtered, and training-ready datasets — with a focus on speed, reliability, reproducibility, and cost-efficiency. You'll partner closely with curation and modeling teams to operationalize evolving dataset recipes and iterate on approaches that improve model outcomes. What You’ll Do: - Design and scale distributed data pipelines for preprocessing, dataset generation, and repeated dataset refreshes - Own workflow orchestration, job scheduling, monitoring, and failure recovery for large-scale data processing jobs - Implement and maintain containerized pipeline infrastructure using Kubernetes or equivalent orchestration systems - Optimize cloud-based data storage and movement across providers (AWS, GCS, or Azure) for cost, throughput, and operational efficiency - Define and implement best practices for dataset storage layout, versioning, caching, retention, and access patterns - Design and implement curation pipelines that determine which video and image content is selected, filtered, and retained for model training, including image-text pair datasets used in joint training regimes - Build and improve VLM-based captioning and metadata generation workflows at scale across both video and image data - Develop and apply quality and aesthetic scoring models, CLIP-based semantic filtering, and other signal-extraction approaches for data selection - Build tooling to support deduplication workflows at scale, including near-dedup and exact deduplication pipelines over large video corpora - Analyze dataset composition, identify quality issues, and iterate on curation logic to improve training outcomes - Define and evolve standards for what constitutes high-quality, training-ready video data across different training regimes What You’ll Bring: - Strong hands-on experience building or scaling large-scale data systems and pipelines for machine learning, including dataset curation, filtering, and quality improvement - Experience with distributed data processing frameworks such as PySpark or Ray, and orchestration tools such as Airflow or equivalent - Familiarity with containerization and container orchestration, including Docker and Kubernetes - Experience working with cloud-based data storage and compute (AWS, GCS, and/or Azure), including tradeoffs around cost, throughput, storage layout, and access patterns - Experience with VLM-based captioning pipelines or quality/aesthetic scoring models for video or image data, including curation of image-text pair datasets for joint image-video training - Familiarity with CLIP-based or embedding-based filtering and semantic data selection techniques - Familiarity with video and media processing tools such as FFmpeg, PyAV, DALI, or OpenCV, and relevant libraries such as Decord, torchvision, PyTorchVideo, or torchaudio - Proficiency in Python - Strong problem-solving, communication, and documentation skills Benefits We Offer: - Competitive salary and generous company equity - Personal time off and paid holidays - Health insurance - Global travel insurance: Covers you when traveling internationally - Monthly spending stipend: $500 (~S$635) - Equipment: All equipment needed for your home office

Location: Brussels, Belgium We currently have a vacancy for a BI Data Engineer (SAP BO) fluent in English, to offer his/her services as an expert who will be based in Brussels, Belgium. The work will be carried out either in the company’s premises or on site at customer premises. In the context of the first assignment, the successful candidate will be integrated in the Development team of the company that will closely cooperate with a major client’s IT team on site and off site. Your tasks Create and maintain the eGrants Enterprise Data Warehouses (EDW); Design Business Intelligence (BI) architectures (e.g., data warehouse, data lakehouses) for cloud, on-premises, and hybrid environments, ensuring compliance with security and data residency requirements. Gather and analyse business requirements specifically for data pipelines, storage, and reporting solutions; Design and implement modern Extract, Transform, Load (ETL) processes and orchestration workflows, incorporating data contracts and schema evolution management; Design and implement data models (e.g., dimensional modelling) to support reporting and analytics, ensuring alignment with business requirements; Design and build reporting and analytics applications, creating dashboards, KPIs, and self- service BI tools that deliver actionable insights to business stakeholders; Design and implement data quality frameworks and health monitoring processes that include data observability (lineage, freshness) and defined Service Level Agreements/Service Level Objectives (SLAs/SLOs); Define and execute test programs for BI solutions, including data validation, regression tests, contract tests, and automated pipelines integrated into CI/CD; Produce and maintain technical documentation (data dictionaries, lineage, design specifications, runbooks) to support transparency, governance, and audit readiness; Govern the BI semantic layer (KPIs, metrics catalog, naming conventions, row-level security) to ensure consistency and trusted insights; Optimize cost and performance of BI platforms and warehouses (partitioning, caching, clustering, query optimization, resource scaling); Enable self-service BI capabilities for business users through curated datasets, certified reports, and training/support. Requirements University degree in IT combined with relevant IT professional experience of at least 10 years; At least 10 years of practical experience with SAP Business Objects is required; At least 8 years of practical experience with SAP Data Services is also Required; Excellent knowledge of enterprise data warehouse design and architecture, including dimensional modelling and star/snowflake schema design; Excellent knowledge of relational database systems applied to data warehousing; Excellent knowledge of SQL and PLSQL; Excellent knowledge of BI reporting and analytics tools (e.g., SAP Business Objects, Power BI, Tableau, Qlik) for enterprise dashboards and self-service analytics; Excellent knowledge of ETL and ELT tools (e.g., SAP DataServices, Informatica, Talend, dbt, Azure Data Factory) to manage enterprise data pipelines; Knowledge of non-relational databases (e.g., MongoDB, Cassandra, Hadoop HBase) for handling unstructured and semi-structured data would be an asset; Knowledge of SAP BO universe design and SAP BO admin; Knowledge of data lake and lakehouse design patterns (e.g., Delta Lake, Apache Iceberg) to support large-scale analytics would be an asset; Knowledge of modelling tools to design data models; Knowledge of OLAP technologies and data mining tools; Knowledge of cloud BI architectures (e.g., Azure Synapse, Snowflake, AWS Redshift) to enable scalable analytics would be an asset; Excellent command of the English language, French will be considered as an asset. Benefits If you are seeking a career in an exciting and dynamic company, where you will offer your services as part of a team of a major European Institution, operating in an international, multilingual and multicultural environment where you can expect real chances to make a difference, please send us your detailed CV in English, quoting reference (21099/10/2026). We offer a competitive remuneration (either on contract basis or remuneration with full benefits package), based on qualifications and experience. All applications will be treated as confidential. EUROPEAN DYNAMICS (ED) ( www.eurodyn.com ) is a leading Software, Information and Communication Technologies company, operating internationally (Athens, Brussels, Luxembourg, Copenhagen, Stockholm, London, Nicosia, Hong-Kong, Valetta, etc). The company employs over 600 engineers, IT experts and consultants (around 3% PhD, 36% MSc and 53% BSc or equivalent). We design and develop software applications using state-of-the-art technology. The group generates annual revenues in the range of EURO 40 million, with an EBITDA in the range of 20%. The value of our contract portfolio exceeds EURO 250 million. EUROPEAN DYNAMICS is a renowned supplier of IT services to government institutions, multinational corporations, public administrations and multinational companies, research and academic institutes. As part of our dedication to the diversity of our workforce, we are committed to Equal Employment Opportunity without regard for race, color, national origin, ethnicity, gender, disability, sexual orientation, gender identity, or religion. EUROPEAN DYNAMICS (ED) adheres to the General Data Protection Regulation principles by applying its Privacy Policy as published in www.eurodyn.com/privacy . By submitting an application to this position and by sharing your personal data with ED, you acknowledge and accept its Policy and authorise ED to process your personal data for the purposes of the company's recruitment opportunities, in line to the Policy. Furthermore, when providing your data, it is up to you to explicitly consent that your data can be assessed for future job openings, for as long as you do not withdraw such consent. If you do not consent, we will not be able to consider the data you provide to us for future job openings.

Location: United States Remote Workplace: Remote ABOUT THE TEAM When the world's largest organizations bet on Mural, Govern & Trust is the team that earns that trust at scale. We build the experiences that help enterprises roll out Mural with confidence, keep it secure, and see the impact it has on how their people work. Data sits at the center of it all. Admins are Mural's most demanding data consumers: they need to prove ROI to their leadership, guide adoption across thousands of people, and account for every action. If data products can meet their bar, they'll work for everyone. Mural has a modern data platform, strong data engineering and analytics teams, and a wealth of data on how teams collaborate. The next step is treating that data as a product in its own right, with a dedicated owner for what it means and how it's used. YOUR MISSION As a Senior Product Manager you'll define the metrics that describe how Mural creates value, and make them the shared foundation for everything built on top. The same definitions will power internal product decisions, the Insights experience Admins use in the product, and the reporting API and MCP server that customers and AI agents query. This role starts upstream. You'll work from raw product events to decide what each metric should measure, how it's calculated, and what the data needs to look like for customers and internal teams to rely on it. Then you'll turn those metrics into experiences that help organizations understand and grow their use of Mural. WHAT YOU'LL DO - The evolution of data products. Shape how Mural's data products move from reporting on what happened to guiding what happens next. Work across the Govern & Trust portfolio to define how insights become part of how organizations run Mural. - The metric layer. Define Mural's shared, cross-product metrics, like activity, collaboration, and adoption. Set the standards that let product teams define and publish their own metrics consistently. Data Engineering builds and runs the layer; you shape what goes in it and how it evolves. - Internal product analytics. Be a thought partner to domain PMs as they set their north-star metrics, and make product data easy for them to explore on their own. Work with Business Analytics to keep product-facing and business-facing reporting working together. - Customer-facing data products. Own the strategy and roadmap for Insights: in-product reporting and dashboards, exports and APIs, audit logs, and the methodology behind every number customers see. - AI and agent access. Package and launch Mural's customer-facing reporting MCP server: which data it exposes, which plans get it, and what guardrails apply. Define how natural-language and agent-driven analysis extends Insights. - Instrumentation. R&D teams own emitting events. Your job is to raise the bar on what they emit. Set per-product requirements for granularity and retention, which differ for audit logs, activity data, and product analytics. Partner with Data Engineering on event standards so metrics start from good data. WHAT YOU'LL BRING - 5+ years of product management experience, including shipping at least one analytics or reporting product used by paying business customers. You defined the metrics behind it, not just the UI. - A track record of making messy or conflicting data trustworthy: reconciling competing definitions, writing metric specs engineers could build from, and getting instrumentation changed upstream. - Experience building both platform products, where your customers are internal teams or developers, and end-user-facing data products like analytics, reporting, or insights. You understand how the two have to work together. - Working knowledge of modern data stacks: event pipelines, warehouses and lakehouses, dbt-style modeling, and semantic layers. You can write SQL and pull data yourself. - The ability to get agreement on definitions across teams you don't manage, including PMs, data engineering, analytics, finance, and go-to-market. - Experience with enterprise admin or governance products (IAM, security, compliance, audit) - Hands-on experience with semantic layer tools (dbt Semantic Layer, Cube, LookML) - Experience designing APIs, MCP servers, or connectors for analytics EQUAL OPPORTUNITY  We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

Location: White Plains, New York Director, Business Intelligence & Reporting Position Overview The Director, Business Intelligence & Reporting, is responsible for leading the strategy, architecture, development, governance, and continuous improvement of enterprise reporting and analytics. This role serves as the organization’s subject matter expert for Microsoft Power BI and bridges complex data infrastructure with executive and operational decision-making. Working closely with Finance, Data Platform, Engineering, IT, Security, and business leaders, the Director will establish scalable reporting standards, consistent KPI definitions, trusted semantic models, and production-grade dashboards that deliver clear, actionable insights. The role will maintain continuity of critical reporting while helping transition manual and legacy reporting processes into a governed enterprise environment. It will also support the broader Enterprise Data Strategy by aligning dashboards, reporting logic, data-quality controls, and source-system reconciliation with the future-state data platform. Primary Responsibilities Enterprise Reporting Strategy & Architecture: Define and execute the enterprise roadmap for Power BI reporting and analytics. Partner with engineering and business teams to transition legacy reporting into scalable semantic models, governed data hubs, and reusable reporting assets. Business Intelligence Delivery: Own the design, development, maintenance, and continuous improvement of enterprise dashboards, recurring management reporting, and executive reporting across Finance, Sales, Operations, Product, and other business functions. Advanced Power BI Development: Architect and deliver complex, interactive Power BI reports and dashboards. Develop optimized DAX calculations and Power Query/M transformations and promote efficient performance across large, multi-source datasets Data Modeling & Integration: Partner with data engineers and cross-functional teams to integrate data from disparate enterprise systems. Design robust dimensional and star-schema models and define clear relationships between reporting outputs and underlying data sources. Reporting Transformation: Lead the transition from manual, spreadsheet-based, and legacy reporting processes toward repeatable, scalable, consistent, and well-documented reporting solutions while maintaining continuity of critical business reporting. Data Quality, Reconciliation & Validation: Establish controls to validate reporting outputs against source systems, agreed business definitions, formulas, and cutoff dates. Identify reporting exceptions and data inconsistencies and coordinate resolution with appropriate data and business owners. KPI & Metric Governance: Partner with stakeholders to establish consistent KPI definitions, calculation methodologies, ownership, lineage, and conflict-resolution processes. Maintain documentation for report logic, source systems, dependencies, and business use. BI Governance & Best Practices: Partner with IT and Security to establish Power BI workspace governance, access protocols, security standards, deployment practices, and performance monitoring. Standardize user experience, visual design, layout frameworks, and calculation conventions. Executive Advisory & Business Partnership: Serve as a strategic advisor to executives and department leaders. Translate high-level business questions into precise analytical requirements and decision-ready dashboards, reports, and insights. Enterprise Data Strategy Alignment: Represent the reporting and analytics workstream within the broader Enterprise Data Strategy. Partner with the Data Platform organization to determine which reporting assets should be retained, redesigned, consolidated, migrated, or retired. Team & Vendor Leadership: Provide technical direction and quality oversight to analysts, developers, consultants, and vendors supporting reporting and analytics. Establish development standards, conduct solution reviews, and promote knowledge transfer and documentation. Innovation & AI Enablement: Evaluate practical emerging capabilities, including AI-assisted analytics, Microsoft Copilot for Power BI, and advanced predictive features, in partnership with Data, IT, Security, and business stakeholders. Minimum Qualifications Bachelor’s degree in Data Analytics, Computer Science, Information Systems, Business Intelligence, Finance, or a related field, or equivalent professional experience. 8+ years of progressive experience in Business Intelligence, analytics, enterprise reporting, or advanced data visualization, including ownership of enterprise-scale Power BI solutions. Expert-level proficiency with Power BI Desktop and Power BI Service, including semantic models, DAX, Power Query/M, gateways, workspaces, security, deployment pipelines, and performance optimization. Advanced SQL proficiency and strong knowledge of dimensional modeling, star-schema design, data warehousing principles, and ETL/ELT concepts. Demonstrated experience reconciling reporting outputs to source-system data and establishing reporting validation and quality-control processes. Experience defining enterprise KPIs, metric standards, reporting governance, documentation, and data lineage expectations. Ability to translate complex business requirements and ambiguous questions into clear technical specifications and decision-useful reporting solutions. Strong executive communication, stakeholder management, analytical, problem-solving, and documentation skills. Experience partnering across Finance, Data, Engineering, IT, Security, Sales, Operations, and Product functions. Preferred Qualifications Experience with Microsoft Fabric or a comparable modern enterprise data platform. Experience modernizing or migrating legacy reporting environments and consolidating redundant dashboards and reports. Experience supporting financial, customer, sales, operational, and executive or Board-level reporting. Experience with enterprise data governance, master data management, data cataloging, or data lineage initiatives. Microsoft Certified: Power BI Data Analyst Associate (PL-300), Fabric Analytics Engineer Associate (DP-600), or comparable credentials. Compensation & Benefits $180,000 – $230,000 annual total compensation (commensurate with experience) Competitive Medical Health Plans, Low, Mid, High. Employer Paid Low Medical Plan for Employee & Dependents (HSA Eligible) Employer Paid Dental & Vision for Employee Employer Paid Life Insurance for Employee Employer Paid Long-term Disability for Employee Employer Paid Hospital Confinement for Employee ~ (If enrolled in Medical) + Voluntary Supplemental Insurance Coverage Options 20 days PTO & 7 Sick Days Annually 10 Fixed Paid Holidays Off Annually 401(k) Matching up to 3% About Us Rectangle Health, a leading financial technology company, empowers medical, dental and specialty practices with seamless and secure technology to drive revenue by increasing patient payments and streamlining practice management and payment processing. Since 1992, the company’s innovative solutions have reduced administrative burden and rebalanced the ledger for its thousands of healthcare providers in the U.S., reliably processing billions of dollars in payments annually. View our CCPA disclosure notice here

Location: Argentina; Ukraine; Poland; Brazil; Georgia; Colombia Workplace: Remote Solvd Inc. is a rapidly growing AI-native consulting and technology services firm delivering enterprise transformation across cloud, data, software engineering, and artificial intelligence. We work with industry-leading organizations to design, build, and operationalize technology solutions that drive measurable business outcomes. Following the acquisition of Tooploox, a premier AI and product development company, Solvd now offers true end-to-end delivery—from strategic advisory and solution design to custom AI development and enterprise-scale implementation. Our capability centers combine deep technical expertise, proven delivery methodologies, and sector-specific knowledge to address complex business challenges quickly and effectively. We are looking for a Senior Data Engineer to join a small, cross-functional engineering team modernizing a data platform for a global financial services client. You’ll be working hands-on with Snowflake and dbt — designing data models, migrating legacy Oracle-based ETL processes, and contributing to architectural decisions alongside client stakeholders. This is a delivery-oriented role with real ownership. You’ll take responsibility for assigned components end to end, participate in client-facing technical discussions, and work directly with both engineering and business teams to define and implement solutions. WHAT YOU’LL DO - Design, develop, and optimize data models and transformation workflows using Snowflake and dbt. - Contribute to the design and implementation of scalable data architecture covering raw through semantic data layers. - Support modernization of existing Oracle-based ETL and reporting processes. - Investigate and address data performance, consistency, and reconciliation challenges. - Develop and maintain data processing, transformation, and automation solutions using Python. - Participate in solution design discussions and contribute to architectural decisions. - Support DevOps-related activities including deployment, configuration, and operational aspects of the data platform. - Take ownership of assigned technical components and deliverables within the team. - Participate actively in client-facing technical discussions and project meetings. REQUIRED SKILLS & EXPERIENCE - Strong hands-on experience with Snowflake — data transformation, modeling, and performance optimization. - Solid understanding of data modeling principles, data architecture, and scalable data solution design. - Practical experience with dbt for developing and maintaining data transformation workflows. - Proficiency in Python for data engineering, scripting, and automation. - Experience with ETL/ELT processes and modern data pipeline development. - Familiarity with DevOps practices and containerized environments including Kubernetes. - Strong analytical and troubleshooting skills around data quality, performance, and reconciliation. - Good communication skills — able to collaborate directly with client stakeholders and participate in regular technical discussions with US-based teams. - English proficiency sufficient for regular technical discussions with US-based teams. PREFERRED QUALIFICATIONS - Experience with Oracle databases, Oracle ETL, and legacy reporting environments. - Prior involvement in data platform modernization or migration from Oracle to Snowflake. - Experience with Power BI and semantic reporting models. - Snowflake professional certification. - Experience designing and optimizing analytical data models for enterprise reporting. - Experience working with distributed, cross-functional engineering teams. - Background in insurance, reinsurance, or financial services. - Availability for occasional business trips to St. Louis, USA — approximately once every three weeks for one to two days. When you join Solvd, you'll… - Shape real-world AI-driven projects across key industries, working with clients from startup innovation to enterprise transformation. - Be part of a global team with equal opportunities for collaboration across continents and cultures. - Thrive in an inclusive environment that prioritizes continuous learning, innovation, and ethical AI standards. Ready to make an impact? If you're excited to build things that matter, champion responsible AI, and grow with some of the industry’s sharpest minds. Apply today and let’s innovate together. Solvd is an equal opportunity employer.

Опыт работы бизнес-/системным аналитиком от 3 лет. • Опыт сбора и анализа требований непосредственно у заказчика.