Вакансии

Компания ВсеИнструменты.ру — один из крупнейших в России интернет-магазинов и омниканальных маркетплейсов, специализирующийся на продаже товаров для дома, дачи, ремонта и строительства. Формат работы: гибридный в Москве.

Wolt развивает платформу быстрой доставки еды, продуктов и других товаров из ресторанов и магазинов через мобильное приложение и сайт. С 2022 года Wolt входит в группу DoorDash и работает в десятках стран. Требования: — 5+ лет опыта — Владение Python или R — Знание SQL — Опыт работы с Airflow Формат работы: удалённо или в офисе в Берлине.

Location: Metn, Lebanon About Toters Toters is an on-demand e-commerce and delivery platform and operates a service that enables customers to get anything in their city at the highest level of convenience. At Toters, technology is at the heart of everything we do. We have product teams that are working hard every day to create products that make our customers' lives easier. Our engineers are also continuously creating solutions to make our processes more efficient, all in an effort to get to our customers fast and at the best cost. If you are interested in working in a high growth startup environment, and look to be part of a team that will potentially change the way customers shop in the Middle East, apply now. The Role As a Senior Analytics Engineer, you will act as the crucial bridge between Data Engineering and Data Analytics. In a fast-paced, high-volume transactional environment like ours, clean, reliable, and scalable data is everything. You will bring software engineering best practices to our analytics workflows, taking ownership of our data warehouse architecture, building robust data models, and designing the ELT pipelines that empower our analysts, data scientists, and business leaders to make high-impact decisions. What You’ll Do Advanced Data Modeling: Design, build, and maintain highly scalable and modular data models using dbt (data build tool) within our cloud data warehouse (e.g., BigQuery, Snowflake, or Databricks), turning raw data into a reliable "single source of truth." Pipeline Optimization: Architect and optimize ELT pipelines to integrate complex, high-volume datasets across our 3-sided marketplace (app clickstreams, operational logistics, merchant catalogs, and financial transactions). Engineering Best Practices: Champion and enforce software engineering practices within the data team, including version control (Git), CI/CD pipelines, code reviews, and writing DRY (Don't Repeat Yourself) code. Data Quality & Governance: Implement rigorous automated testing, alerting, and anomaly detection to guarantee data integrity and build trust with downstream stakeholders. Self-Serve Enablement: Design intuitive semantic layers and heavily documented data marts that empower Product Analysts and Business operators to independently explore data without writing complex SQL. Performance & Cost Optimization: Audit and optimize legacy queries, streamline warehouse compute resources, and ensure BI tools (Tableau) run with minimal latency. Mentorship: Elevate the technical baseline of the entire Data Analytics team by teaching advanced SQL, dbt modeling techniques, and performance-tuning strategies. What We’re Looking For Experience: 4+ years of experience in Analytics Engineering, Data Engineering, or a highly technical Data Analytics role, ideally within a high-growth tech company, delivery platform, or multi-sided marketplace. SQL & dbt Mastery: Unmatched proficiency in writing complex, highly performant SQL. Extensive, hands-on experience building production-grade environments in dbt (including Jinja, macros, and incremental logic). Cloud Data Warehousing: Deep conceptual and practical understanding of modern columnar data warehouses (Snowflake, BigQuery, or Databricks) and architecture best practices. Software Engineering Mindset: Fluent in Git workflows, command-line interfaces, and setting up CI/CD workflows for data deployments. Programming Skills: Strong proficiency in Python for API integrations, custom transformations, or pipeline scripting. Business Acumen: Demonstrated ability to translate complex operational logic (e.g., courier dispatch algorithms, funnel attribution, financial reconciliation) into elegant data architecture. Nice to Have Hands-on experience with modern data orchestration tools (Apache Airflow, Dagster, or Prefect). Experience managing event-tracking pipelines (Snowplow, Segment, Amplitude). Previous experience managing the semantic layer in BI platforms like Tableau.

Location: San Francisco, California Workplace: Hybrid ABOUT SENTRY Software runs the world and the pace is faster than ever. Sentry helps developers fix errors and performance issues before users notice, so teams can spend less time firefighting and more time building. Trusted by 200,000+ organizations, Sentry is today’s application monitoring standard and our team is building its AI-native future. ABOUT THE ROLE Sentry provides developer-first observability to over 4 million developers worldwide. The Events Analytics Platform (EAP) team is at the heart of that mission: it powers how all of Sentry's event data, such as errors, transactions, spans, profiles, replays, and metrics, is stored, queried, and analyzed. It also powers Sentry's latest AI push, Seer. The EAP team makes it possible for developers to efficiently search and debug across massive volumes of data, providing the context needed to understand and fix issues quickly. This team is also a cornerstone of Sentry's long-term strategy to become a context assembly and telemetry platform that unifies different signals so developers can see the complete picture. As an engineering manager on the EAP team, you will lead a group of engineers building and scaling one of Sentry's most critical data platforms. You will be responsible for driving architectural evolution, ensuring system stability, and mentoring a talented team. This is a highly visible leadership role with direct ties to Sentry's long-term product and platform strategy. WHAT YOU'LL DO - Grow and develop a team of engineers with high expectations for ownership and impact - Set the technical and strategic direction for the team, balancing short-term stability with long-term architectural evolution - Drive development of core EAP features, including support for complex analytical queries, dynamic routing logic across fidelity levels, storage and compute separation, and modern patterns for analytical storage - Ensure EAP can support the workload demands of AI agents and MCP servers that unlock new AI capabilities for Sentry - Guide the unification of all event data into EAP and enable fast, complex cross-event querying at scale - Partner closely with cross-functional teams including Product Engineering, Streaming, Production Engineering, Security, and Compliance - Lead the team through incidents, postmortems, and scaling challenges while fostering operational excellence - Build a healthy and collaborative team culture rooted in growth, accountability, and inclusion YOU'LL LOVE THIS JOB IF YOU - Enjoy mentoring and developing engineers, especially helping junior engineers grow into senior roles - Get excited by designing and running large-scale distributed data systems where performance and reliability matter - Are passionate about tackling the challenges of continuously scaling as Sentry's traffic grows - Like tackling complex querying and storage challenges at massive scale - Thrive on cross-functional collaboration with product and infrastructure teams - Want to work on a highly strategic team with significant visibility that shapes the future of Sentry's platform QUALIFICATIONS - 10+ years of industry experience in software engineering, including 4+ years of people management experience with career development and performance management - Strong technical background in data platforms, storage systems, or analytical backends (for example, ClickHouse, Pinot, or Druid) - Experience with distributed systems, query optimization, or scaling data-intensive workloads - Excellent communication skills with the ability to clearly articulate technical concepts to diverse audiences - Proficiency with Python, Rust, or a similar programming language is a plus - Familiarity with observability, developer tools, or event-driven systems is a plus The base salary range that Sentry reasonably expects to pay for this position is $220,000 to $400,000 USD, plus an annual performance bonus of up to 15% of base salary. A successful candidate’s actual base salary (or hourly wage) amount will be determined by a variety of relevant factors including, without limitation, the candidate’s work location, education, work and other relevant experience, skills, and job-related knowledge. A successful candidate will be eligible to participate in Sentry’s employee benefit plans/programs applicable to the candidate’s position (including incentive compensation, equity grants, paid time off, and group health insurance coverage). See Sentry Benefits https://sentry.io/careers/ for more details about the Company’s benefit plans/programs. EQUAL OPPORTUNITY AT SENTRY Sentry is committed to providing equal employment opportunities to its employees and candidates for employment regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, or other legally-protected characteristic. This commitment includes the provision of reasonable accommodations to employees and candidates for employment with physical or mental disabilities who require such accommodations in order to (a) perform the essential functions of their jobs, or (b) seek employment with Sentry. We strive to build a diverse team, with an inclusive culture where every teammate can thrive. Sentry is an open-source company because we believe that everyone, everywhere, should have the ability and tools to make great software. Software should be accessible. That starts with making our industry accessible. If you need assistance or an accommodation due to a disability, you may contact us at accommodations@sentry.io. Want to learn more about how Sentry handles applicant data? Get the details in our Applicant Privacy Policy https://sentry.io/careers/applicantprivacy/.

Location: London, United Kingdom - Deliveroo Our Global Structure Deliveroo is now part of DoorDash, bringing together teams with even greater reach, scale, and ambition. Depending on your role, you may collaborate with teammates, systems, and leaders across DoorDash and Wolt. Together, we’re unlocking new possibilities as one global team. Join us in our mission to transform the way people shop and eat, where impact, innovation and growth drive everything we do. Our Engineering teams tackle complex technical challenges across a global, three-sided marketplace, building and scaling systems that serve millions of customers, riders and partners every day. From real-time logistics to resilient infrastructure and marketplace optimisation, we design, build and operate technology that powers Deliveroo’s growth at scale. We’re looking for a BI Engineer to join our London team. This role is based in our London office with a hybrid setup, typically 3 days in the office. Get to know our Engineering team — what drives us, how we work, and what you can expect. About the Team The Core BI team builds and operates the services, integrations and automation that power business intelligence across DoorDash, Deliveroo and Wolt. Our platforms help analysts, Analytics Engineers, Data Scientists, Software Engineers and business teams discover trusted data and make informed decisions at scale. We combine software engineering, platform ownership, and a strong user focus to make BI tooling reliable, secure, scalable and self-service. The team supports the current BI ecosystem while helping shape a more integrated experience across the DoorDash group. About the Role As a BI Engineer on the Core BI team, you will build and operate the models, systems and automation behind our BI platforms. This will include supporting our extensive user base on our current BI stack (primarily Looker and Sigma) while helping shape a single, more integrated BI platform across DoorDash, Deliveroo and Wolt. You will own problems from discovery through design, implementation, deployment, and operational support. You will work closely with Data Engineers, Analytics Engineers, Data Scientists, Software Engineers, Product Managers and business teams to turn recurring user needs into durable, self-service capabilities. If you're energized by solving technical problems with data and comfortable being deeply embedded across several domains, this role is for you! You’re excited about this opportunity because you will… Own and evolve the semantic layer behind our BI platforms: LookML and Canvas BI models, metric and dimension definitions, and the governance that keeps them trusted Build and operate the Looker and Sigma platforms themselves: instance and workspace configuration, permissions and user attributes, content lifecycle, and API-driven automation Lead the development of self-serve tooling that removes manual BI administration, using usage analytics to decide what to automate, build or retire next Support BI platform migrations and deprecations across DoorDash, Deliveroo and Wolt while protecting access, governance, data integrity and business continuity Take part in operational support, production debugging and incident response for the BI stack, and fix the root causes you find Champion engineering standards in BI, including version control, code review, CI and testing for models and platform code, so changes ship safely and repeatably We’re excited about you because… 3+ years of experience in business intelligence engineering, analytics engineering, data engineering, or a similar code-first data role Strong Python and SQL skills, and hands-on experience using AI tools (LLMs, agentic workflows, AI-assisted development) to accelerate your own engineering work Hands-on experience building in a BI platform such as Looker (LookML) or Sigma, modelling and configuring it, not only building dashboards in it Experience with semantic or metrics layers (LookML, dbt or similar): defining metrics and dimensions, and keeping those definitions consistent as they are reused Experience running what you build in production: version control, code review, CI, debugging live issues and taking part in operational support Excellent communication skills, and comfortable self-organising in a fast-paced, distributed environment with both technical and non-technical teams Nice to Have Experience with modern data warehousing platforms (e.g., Snowflake, Databricks, Redshift) and ability to optimize performance Experience automating BI administration through platform APIs, or identity and access through Okta, SCIM or role-based access controls Experience supporting a BI stack across multiple brands, tenants or regions, or leading a BI platform migration Why Join Us? At Deliveroo, you’ll do work that matters—solving real-world problems in a three-sided marketplace that’s constantly evolving. We’re food lovers, problem solvers, community builders and more, brought together by a shared drive to make things better. Working here you can expect to: 🔧 Solve meaningful problems at real scale Work on a complex, always-on marketplace that impacts millions every day. 🌱 See your impact, fast Ship, test and improve ideas quickly in a low-hierarchy, high-ownership environment. 🧠 Grow through challenge and ownership Take on big, ambiguous problems and accelerate your career with strong support. 🌎 A culture built for builders High standards, collaboration, flexible working and continuous learning. ➡️ Want a deeper look at how we build? Check out our Tech Blog . We aim to create a fair process that lets your skills shine—our interview typically includes 3-4 stages. Explore our Engineering Interview Guide here to help you feel confident at each stage. Our Global Structure Deliveroo is now part of DoorDash, bringing together teams with even greater reach, scale, and ambition. Depending on your role, you may collaborate with teammates, systems, and leaders across DoorDash and Wolt. Together, we’re unlocking new possibilities as one global team. Diversity, Equity and Inclusion At Deliveroo, we know that a great workplace reflects the world around us and that true diversity and inclusion make us stronger, more creative, and better at what we do. We’re committed to fostering an environment where everyone can do their best work and feel they belong. We believe in equality of opportunity and welcome candidates from all backgrounds regardless of age, gender, ethnicity, disability, sexual orientation, gender identity, socio-economic background, religion, or belief. If you have a disability or long-term health condition and need support to apply for one of our roles, or require any reasonable adjustments during the recruitment process, you’ll have the opportunity to let us know once you’ve submitted your application. We’ll share details on how to request support so we can ensure you have a fair and equitable experience. If you’re excited about making a real impact in a fast-moving marketplace and growing your career alongside ambitious, supportive teams, we’d love to hear from you! Beware of recruitment scams: DASH Brands will never ask you to pay money or share sensitive financial information during hiring — learn more about DASH Brands' legitimate recruiting process at careersatdoordash.com/recruitment-scam-awareness .

We are building a new capability that turns fragmented, noisy security logs into actionable insights. The position is full-time, 40 hours per week, with mostly remote work within Germany and monthly in-person collaboration at the Berlin office. The contract is fixed-term. Salary ranges from EUR 69,000 to 77,000 per year.

Location: United Kingdom, London Why Sony Interactive Entertainment? Sony Interactive Entertainment isn’t just the Best Place to Play — it’s also the Best Place to Work. Sony Interactive Entertainment (SIE) is the company behind the PlayStation brand. As a subsidiary of Sony Group Corporation, we’re part of a proud legacy of innovation and excellence. SIE is a dynamic technology company, delivering cutting-edge hardware and network services to more than 100 million people and an entertainment leader, home to some of the most beloved and recognizable intellectual properties (IP) in the world. Our role at SIE is to create and nurture the experiences under the PlayStation brand, a name synonymous with entertainment excellence and creativity. Role Overview: We are seeking a Senior Director to lead our Enterprise Reporting and Analytics Engineering organization, a team of analytics engineers, report developers, visualization specialists, and people leaders. This organization focuses on the last mile of the enterprise data supply chain: the semantic models, curated data products, metric definitions, and consumption experiences that turn engineered data into decisions. This is not a traditional reporting leadership role; the classic notion of “reporting” in the form of a myriad of dashboards and filters is racing towards obsolescence. But the need for data and insights, and the need to deliver it in a way that is digestible and actionable, is timeless. Yes, governed dashboards and trusted reporting remain the foundation, and this leader must be excellent at that foundation. But the mandate is to move the organization decisively beyond static reporting toward a proactive, intelligent analytics capability: partnering with Data Science to productize and visualize their models, enabling generative AI and LLM-based access to our data, building exception-based systems that alert users when outcomes deviate from expectation in a statistically meaningful way, and designing agents that monitor data continuously and deliver insight without being asked. Analytics engineering shares much of its DNA with data engineering — modeling, transformation, testing, version control, CI/CD, performance and cost discipline — but is oriented toward business enablement rather than platform and pipeline. Success in this role therefore depends as much on partnership as on technical depth. This leader will work shoulder to shoulder with Data Engineering on the boundary between platform and consumption, with Product Management on roadmap and requirements, with Data Science on advanced analytic products, and with Analytics Operations on a disciplined intake and prioritization process that makes the best possible use of finite capacity. The ideal candidate has spent years building the traditional foundations — governance, metadata, lineage, dimensional modeling, engaging with enterprise BI platforms— and is now looking to apply that rigor to a fundamentally different generation of analytic products in new and innovative ways. What you'll be doing: Organizational Leadership Lead, coach, and develop an organization of approximately 30 people, including managing through frontline managers; own hiring, role clarity, career pathing, performance management, and succession planning. Define a multi-year vision and roadmap for enterprise reporting and analytics engineering, and translate it into quarterly outcomes the team and its partners can measure. Partner closely with Product Management to jointly shape the multi-year enterprise end-to-end data strategy. Own the organization's budget, vendor relationships, and contractor or offshore capacity. Establish and sustain an engineering culture within an analytics function: peer review, automated testing, documentation standards, source control, CI/CD, etc. Analytics Engineering and Data Architecture Drive maturity of the last-mile architecture in partnership with Data Engineering: curated marts, semantic layers, reusable data products, and certified datasets that serve reporting, ai enablement, data science, and downstream applications. Define and enforce dimensional modeling standards, transformation frameworks, and modular, tested, version-controlled analytics code. Own the enterprise metric layer so that key business measures carry a single, governed definition regardless of where they are consumed. Partner with Data Engineering to define clear contracts and handoffs between pipeline and platform work and last-mile modeling, including shared tooling, standards, and escalation paths. Manage query performance, warehouse consumption, and platform cost as first-class engineering concerns. Data Governance, Metadata, and Lineage Own cataloging, business glossary, data certification, and stewardship workflows, leveraging tools such as Atlan as the primary metadata platform. Maintain column-level lineage across the analytics estate to support impact analysis, change management, audit, and root-cause investigation. Leverage data access provisioning and entitlement models, including row- and column-level security, in partnership with Security, Privacy, and Compliance. Collaborate with Data Engineering to drive data quality monitoring, freshness and availability SLAs, observability, and incident response for analytic assets. Enterprise Reporting and Data Visualization Drive analytics engagement by leveraging enterprise visualization and provisioning platforms, including Domo and Tableau, in partnership with Data Engineering. Ensure best practices are followed in data architecture, governance, adoption, performance, and total cost management. Set visualization and information design standards that make reports readable, consistent, accessible, and decision-oriented. Rationalize the existing reporting portfolio: retire redundant and unused assets, consolidate overlapping content, drive down tech debt and drive consumption toward certified sources. Build a durable self-service capability through training, templates, community, office hours, and clear guardrails on what belongs in self-service versus centrally managed content. Advanced, Proactive, and AI-Enabled Analytics Partner with Data Science to productize their work: build the visualization, interaction, monitoring, and feedback loops that turn models and research into products the business actually uses. Partner with Product Management and Data Engineering to enable generative AI and LLM access to enterprise data. This includes preparing the semantic and metadata foundation that makes data legible to models, delivering conversational analytics, text-to-SQL, and retrieval-augmented experiences on governed sources, and establishing guardrails, evaluation, and accuracy monitoring so that answers can be trusted. Build exception-based analytics that detect when an outcome deviates from its expected value in a statistically significant way, using seasonality-aware baselines, forecast residuals, control limits, and anomaly detection rather than static thresholds. Route those exceptions to accountable owners with context, likely drivers, and a recommended next action; actively tune sensitivity and volume to prevent alert fatigue and preserve signal. Design and deploy analytic agents that proactively monitor data, investigate variances, assemble narrative explanations, and deliver insight into the tools where people already work. Shift the organization's consumption model from pull to push: the measure of success is not how many people opened a dashboard, but whether the right person was told the right thing at the right time. Cross-Functional Partnership, Intake, and Prioritization Operate as a true partner to Product Management: contribute to roadmap, requirements, user research, and release planning, and run analytics with a product mindset covering personas, adoption metrics, and asset lifecycle management. Partner with Analytics Operations to run a transparent intake, triage, sizing, and prioritization process, with published capacity, explicit tradeoffs, and reliable delivery commitments. Make capacity constraints visible to stakeholders and executives, drive reuse over one-off builds, and decline or defer work with evidence rather than friction. Serve as a senior, executive-facing partner to business functions, translating ambiguous business questions into well-scoped analytic solutions. What we're looking for: Bachelor's degree in Computer Science, Information Systems, Engineering, Statistics, Mathematics, Economics, or a related quantitative field; equivalent professional experience will be considered. 15+ years of progressive experience in data, analytics, or business intelligence, including 8+ years leading teams and 4+ years managing managers. Demonstrated experience leading an organization of 25 or more people in a large, matrixed enterprise. Strong hands-on foundation in SQL, dimensional modeling, and ELT/ETL design, with production experience on a modern cloud data warehouse or lakehouse (for example Snowflake, Databricks, BigQuery, Redshift, or Synapse) and a transformation framework such as dbt. Experience applying software engineering practices to analytics work, including Git-based workflows, automated testing, and CI/CD. Enterprise-scale leveraging of BI and data visualization platforms such as Domo, Tableau, Power BI, or Looker, including governance, provisioning, adoption, and cost management. Demonstrated ability to participate in driving data governance program covering catalog, lineage, glossary, stewardship, quality, and access, using platforms such as Atlan, Collibra, Alation, or Informatica. Proven track record of delivering jointly with Data Engineering and Product Management, with clear ownership boundaries and shared accountability. Direct experience partnering with Data Science, including operationalizing, visualizing, and monitoring model output for business consumption. Working command of the statistical concepts underlying exception detection, including hypothesis testing, confidence intervals, variance and control limits, seasonality, and forecasting. Experience running a formal intake, prioritization, and capacity planning process for a shared services or platform organization. Excellent executive communication and influence skills, with the ability to operate effectively amid ambiguity and competing priorities. Experience managing budget, vendor contracts, and platform licensing. Preferred Skills: Master's degree or MBA in a related field. Production experience delivering LLM-based analytics: retrieval-augmented generation over governed data, text-to-SQL or conversational BI, semantic layers designed for model consumption, and prompt, evaluation, and cost monitoring frameworks. Experience designing agentic workflows and orchestration for monitoring, investigation, and notification use cases. Hands-on experience with Atlan, Domo, and Tableau specifically. Proficiency in Python or R for prototyping, and familiarity with common statistical and ML libraries and MLOps concepts. Experience deploying anomaly detection at scale, including alert routing, suppression, and fatigue management. Familiarity with data product and data mesh operating models, domain-aligned ownership, and data contracts. Experience operating in an Agile or product operating model at scale, including portfolio, OKR, and roadmap management. Deep experience with the “Silicon Valley” school of Product Management, as exemplified by the “Marty Kagan”-style academic approach a significant plus. Experience leading global or matrixed teams, including offshore or vendor-partnered delivery models. Track record leading a major platform migration, consolidation, or reporting rationalization effort. Demonstrated success attracting, developing, and retaining senior technical talent in a competitive market. Please note, Sony Interactive Entertainment conducts background checks at the offer stage for all new employees (which may include criminal background checks for some roles) and will need to process personal information to support these checks. Please refer to our Candidate Privacy Notice for more information about what personal information we collect, how we use it, who we share it with, and your data protection rights. Equal Opportunity Statement: Sony is an Equal Opportunity Employer. All persons will receive consideration for employment without regard to gender (including gender identity, gender expression and gender reassignment), race (including colour, nationality, ethnic or national origin), religion or belief, marital or civil partnership status, disability, age, sexual orientation, pregnancy, maternity or parental status, trade union membership or membership in any other legally protected category. We strive to create an inclusive environment, empower employees and embrace diversity. We encourage everyone to respond. Sony Interactive Entertainment is a Fair Chance employer and qualified applicants with arrest and conviction records will be considered for employment.

Задачи: — Владение и управление тремя связанными продуктами: Predictions, Analytics и A/B testing. — Руководство небольшой командой ML, определение задач и подбор новых участников. — Управление prediction engine: определение прогнозов, требований к точности и доказательств для клиентов. — Анализ и улучшение производительности дашбордов, чтобы повысить их использование. — Решение о внедрении ML возможностей в продукты или отказ от них. Требования: — Практический опыт работы с кодом или моделями, достаточный для самостоятельного принятия технических решений. — Сильные знания математики и классического машинного обучения, умение обсуждать выбор моделей, метрики и горизонты. — Опыт владения продуктом, а не только бэклогом, с конкретными результатами. — Владение SQL и привычка самостоятельно проверять данные. Условия: — Работа с сильным продуктом с лучшими в индустрии метриками, компания входит в топ 5% быстрорастущих SaaS. — Исключительное вознаграждение, напрямую связанное с результатами. — Прямое общение и владение процессами без бюрократии и политики. — Гибкий удалённый формат работы или работа в офисах в Белграде или Лондоне. — Профессиональная поддержка: изучение языков, спорт, медицинская страховка, покрытие расходов на ноутбук и другое.

About LawnStarter LawnStarter is the nation's leading on-demand marketplace for lawn care and outdoor services, with over $100M in annual bookings. The company is expanding beyond lawn care to become a one-stop shop for all home services, operating across three brands (LawnStarter, Lawn Love, Home Gnome) on a single shared platform. About Analytics at LawnStarter The analytics team supports the entire company including product, marketing, operations, and finance. The data platform includes a centralized Redshift data warehouse, modeled in dbt and orchestrated by Airflow, with Segment feeding event data. The team is mid-migration to Lightdash as the single BI platform, replacing Tableau and Metabase. Currently, data quality, tracking standards, and platform hygiene are side tasks handled by analysts. The Role The Analytics Engineering Manager will be the first dedicated person for data governance, responsible for data trustworthiness and the roadmap to improve it quarterly. Responsibilities include ensuring quality and freshness of source data, pipelines, reports, metric definitions, Segment event tracking standards, Lightdash workspace health, data feeding ML models, and data security. The role involves collaborating with product, marketing, ops, and finance to prioritize platform work. It is a hands-on role starting solo, building automation, checks, fixing issues, and establishing scalable processes. Eventually, the manager will hire a Lead Analytics Engineer and grow the function as needed. Key differentiators of the role: - First dedicated governance role, reshaping existing standards. - Owns the data roadmap, discovering business needs and prioritizing work. - Whole-stack ownership from source data to ML models. - Leading the migration to Lightdash, setting up permissions and norms. Responsibilities: - Develop and manage the data roadmap balancing business needs and platform health. - Automate monitoring of data quality and freshness, resolve incidents. - Maintain data lineage and impact analysis to assess downstream effects of changes. - Administer Lightdash workspace, permissions, and rollout. - Extend and guard the semantic layer with governed metric definitions. - Govern Segment event tracking catalog, standards, and drift detection. - Ensure AI data readiness for internal AI tools querying the warehouse. - Manage data security, privacy, access controls, and compliance with US state laws. - Maintain governance documentation, ownership models, and review processes. Challenges to solve: - Convert business requests into a prioritized data roadmap. - Ensure Lightdash migration improves platform usability without dashboard sprawl. - Complete and maintain a trustworthy semantic layer. - Manage event-tracking standards and prevent entropy. - Proactively detect and prevent data pipeline breakages with automation and lineage. Success metrics for year 1: - Zero pipeline incidents from unannounced data changes. - Zero freshness incidents; stakeholders never see stale dashboards. - All business areas use official, well-maintained metrics and dashboards. - Every Segment event has an owner and meets standards. - Governance operates as a documented, sustainable system. Requirements: - Passion for data governance as a craft. - Daily use of AI tools for automation, anomaly triage, and documentation. - Hands-on manager who codes, debugs, and configures personally. - Product-minded, able to translate vague requests into prioritized plans. - Automation-first approach to quality checks. - Ability to enforce standards with clear rules and good tooling. Role exclusions: - Not a large-team leadership role; starts solo with potential to hire one lead. - Not a policy or committee role; hands-on fixing with code and conversations. - Not a BI analyst role; focuses on platform and guardrails, not dashboard building. - Not a mature system babysitting role; involves building and evolving the platform. Technologies involved: - Warehouse & pipelines: Redshift, dbt, Airflow - Ingestion: Fivetran, custom Airflow pipelines - Event tracking: Segment - BI tools: Lightdash (primary), Tableau and Metabase (sunsetting) - AI tooling: Claude Code, Codex, Brain (internal AI toolkit) - Observability: AI-powered Analytics Engineer agent for monitoring and anomaly detection Benefits: - Base salary $75k-$120k/year - Fully remote with asynchronous collaboration - Flexible PTO Equal employment opportunity statement included.

Задачи: — Владение дорожной картой данных: выявление потребностей продукта, маркетинга, операций и финансов в данных, приоритизация задач с учетом состояния платформы и последовательное планирование инвестиций. — Обеспечение качества и актуальности данных: автоматический мониторинг источников данных, конвейеров и отчетов, выявление изменений в схемах и источниках до возникновения проблем, управление инцидентами. — Анализ происхождения данных и влияния изменений: создание живой карты от источника до отчетов, оценка влияния изменений на downstream компоненты до их внедрения, внедрение контрактов данных с инженерией. — Администрирование Lightdash: настройка структуры рабочего пространства, прав доступа, обучение пользователей, поддержание порядка и производительности. — Управление семантическим слоем: расширение и поддержка единого определения метрик, предотвращение неконтролируемого роста. — Управление каталогом событий Segment: проверка новых событий на соответствие стандартам, поддержание соответствия с продакшеном, развитие правил и обнаружение отклонений. — Обеспечение готовности данных для AI: контроль доступа AI-инструментов к данным, поддержание документации, консистентности и безопасности. — Обеспечение безопасности и конфиденциальности данных: контроль доступа, обработка персональных данных в соответствии с законами штатов США, регулярные проверки. — Поддержка системы управления: документация, модели владения и циклы обзора для устойчивой работы процессов. Требования: — Профессиональное отношение к управлению данными, стремление к поддержанию чистоты и надежности систем. — Активное использование AI-инструментов для автоматизации проверок, обработки аномалий и документации. — Практический опыт управления командой и самостоятельной работы с SQL, Airflow, настройкой прав доступа. — Ориентация на продукт, умение превращать запросы бизнеса в приоритетный план. — Стремление к автоматизации повторяющихся проверок. — Умение устанавливать стандарты и добиваться их соблюдения с помощью инструментов и коммуникации. Условия: — Базовая зарплата $75,000-$120,000 в год. — Полностью удаленная работа с асинхронным взаимодействием. — Гибкий отпуск по результатам работы. Описание роли: — Первая позиция, посвященная управлению данными и их качеством в компании. — Роль с полным владением цепочкой данных от источника до отчетов и моделей машинного обучения. — Роль с практической деятельностью и последующим расширением команды. — Не руководящая большая команда, а построение и развитие функции. — Не роль BI-аналитика или политика, а инженерно-управленческая позиция. Технологии: — Хранилище и конвейеры: Redshift, dbt, Airflow. — Интеграция данных: Fivetran, кастомные Airflow конвейеры. — Отслеживание событий: Segment. — BI-платформы: Lightdash (основная), Tableau и Metabase (выводятся). — AI-инструменты: Claude Code, Codex, Brain (внутренний AI-инструмент). — Наблюдение: AI-агент для мониторинга свежести, обнаружения аномалий и lineage dbt.

Location: Americas; EMEA Workplace: Remote RevenueCat gives app businesses the infrastructure and tools to build, run, and improve their monetization. Since graduating from YC's S18 batch, we've grown into the default monetization platform for mobile. We're in 50%+ of newly shipped subscription apps, we process $16B+ in annual purchase volume, and we help everyone from a solo developer to the OpenAI mobile team understand and grow their revenue. We're a remote-first team of 150+ people across 25+ countries, guided by values we actually practice: Customer Obsession, Always Be Shipping, Own It, and Balance. This isn't the right fit for everyone. The systems you’ll build here manage billions of dollars and touch hundreds of millions of end users, and we don’t take that lightly. You'll be expected to work hard and hold a high bar for what you ship, alongside some of the sharpest, most driven people you've worked with. If that sounds energizing rather than exhausting, keep reading. ABOUT THE ROLE We're looking for a Senior Product Manager to join the team working on analytics features in RevenueCat. RevenueCat is the monetization engine for 40% of new subscription apps shipped — and the number of apps shipped is growing exponentially. We are uniquely positioned not only to give individual developer impactful information into the performance of their own apps, but also deliver truly unique data and insight given our position in the market; we know what good looks like, and we can not only put numbers in context, but give specific recommendations on metrics to target, experiments to run and anomalies to investigate. Our analytics features help app developers make better decisions that improve the monetization of their apps. As product manager on this team, you are responsible for working with your team to set the vision and roadmap, delivering on it, launching new functionality, and increasing the impact of the team. This role requires: - being technical to understand how our analytics system works and its constraint - being analytical to be able to define how to show data as well as debugging issues and edge cases - being customer obsessed to understand what information app developers need for their decisions and how we can provide this information to them - having an understanding of the app ecosystem, how the economics of app businesses work, and what success means for app developers You will oversee all of the Analytics features at RevenueCat — our charts, benchmarking, dashboard, and predictive LTV. You'll partner directly with leadership, collaborate across engineering and data teams, and act as the primary driver for how our customers understand and grow their revenue. ABOUT YOU Skills & Experience - You have 5+ years of product management or adjacent experience, with meaningful time shipping complex products. - You’re analytical. You can’t do your job without data platform access. You are proficient in SQL (or similar tools) — whatever tool you need to know, you’ll learn. You love diving deep into data yourself. You’re experienced in developing robust and scalable metrics. - You are technical. Coding is not a core requirement for this role, being able to prototype with code is (using your preferred AI stack). You can deeply understand how RevenueCat works — what is simple and what is complex within our domain. Maybe you haven’t built and shipped a mobile app yourself (yet) but you have enough knowledge to work closely and independently with highly technical folks. You can discuss APIs, data models, and risk logic with engineering partners and enjoy diving into system details - You’re an excellent communicator. You can express complex ideas clearly and succinctly — written and verbal, synchronous and asynchronous, across timezones and mediums. You can get your point across. Values and Abilities - You act like an owner. You roll up your sleeves, dive into the logs, and get something done yourself. - You thrive in ambiguity. You are comfortable making low-information, high-stakes decisions. You can quickly get to confidence, move on, and iterate. - You're a systems thinker. You can step back from a specific customer request and see the broader system. You build things that scale. - You're deep on the details. You care about what users experience, not just what the data says. - You know when it's good enough. You are obsessed with getting things right, but you know when you're at diminishing returns. You have a bias toward shipping. You love building — and are energized by discovery, experimentation, and rapid iteration. - You’re passionate about great data visualization. Chart sins grind your gears. Your visualizations deliver meaningful insights. You care what is says — and what it looks like — and you know those things are dependent on each other. WHAT YOU'LL DO - Own the product strategy and roadmap for RevenueCat's Analytics products. - Be obsessed with your customers. You will triage and investigate complex data and analytics problems deeply, instead of fully delegating to engineering. Dig deep to understand what developers really want — distill signal from noise and good ideas from bad ones. - Recommend, develop and maintain new benchmarks and metrics that deliver value to our developers, and help them make more money. Be the go-to person when a number looks off. - Set the vision. Create a plan that is cohesive, intentional, and impactful. Break that down into meaningful chunks on a reasonable timeline. - Get it done. Collaborate closely with engineering, data science, and GTM teams to bring robust analytics and experimentation tools to market. This job can not be done alone, and will require deep understanding of the individual products and the infrastructure that hooks them together. The salary for this role is $230,000 USD. You can view our full Compensation Philosophy here https://www.notion.so/revenuecat/RevenueCat-Compensation-Philosophy-82b57cae23ab4c9bb62dfe4e933d32d0 for additional details. In the first month, you'll: - Get to know the product, customers, and team - Contribute to shipping a meaningful feature to thousands of developers - Be ramped up on ongoing projects in your teams Within the first 3 months, you'll: - Have formed a strong working relationship with your engineering manager and design counterpart - Have taken ownership of the roadmap and prioritization for your team (jointly with the engineering manager) - Work with your engineering manager and leadership to define quarterly objectives for your teams - Have shipped the first bigger feature end to end - Work with your team to discover opportunities and solutions to deliver value to our customers - Play an integral role in your team’s discovery and delivery processes - Understand the fundamentals of our tech stack and its complexities, and drive the evaluation feasibility/value tradeoffs in collaboration with your teams Within the first 6 months, you'll: - Have helped your team grow and become a high-performing, engaged team in line with our company values - Effectively collaborate with internal stakeholders of all levels - Be an expert of your areas of the product and the related customer needs, and instill customer empathy in your teams - Independently drive all product-related decisions in your area - Have contributed meaningfully to our knowledge of our customers and their needs, our industry, and important trends - Develop a longer term vision for your area of the product in line with the product strategy - Work with your teams to improve processes and interfaces with other teams Within the first 12 months, you'll: - Be ready to kill something you have shipped if we learned it didn't deliver the value we hoped - Explore completely new opportunities for how RevenueCat may provide greater value to our customers - Make meaningful contributions to our overall product strategy - Have delivered a material, business-impacting new benefit to our customers in your product area WHAT WE OFFER: - Competitive equity in a fast-growing, Series C startup backed by top-tier investors, including Y Combinator - 10-year window to exercise vested equity options - A fully remote environment designed around autonomy and flexibility - 4-5 weeks of flexible time off annually - Paid desk at a co-working space - Workspace budget and continuous learning stipend INTERVIEWING AT REVENUECAT Our interview process is rigorous on purpose. We want to be sure that everyone we bring on is genuinely excited about this work, aligned with how we operate, and ready to meet our high bar for performance. Curious what that actually looks like? Read more in our blog post on how we hire at RevenueCat https://www.revenuecat.com/blog/company/how-we-hire-at-revenuecat/, including tips to help you succeed. MORE ON HOW WE WORK: - How we think about hiring and team design: Building a Winning Team https://app.notion.com/p/Building-a-Winning-Team-69e431c4c3df4b13961523cd93c0e9bf?pvs=21 - The values that guide how we work: Our Values https://www.revenuecat.com/blog/values/ - How we work as a remote team: How We Work Remotely at RevenueCat https://www.revenuecat.com/blog/how-we-work-remotely-at-revenuecat/ - What to expect from our interview process: Interview Expectations https://app.notion.com/p/RevenueCat-Interview-Expectations-1bdcb1a108b0800c8941def0f076f9e2?pvs=21 - What to expect from comp and employment: Employment FAQ https://app.notion.com/p/RevenueCat-Compensation-Employment-Overview-184cb1a108b0801398d4e525928597ab?pvs=21

Location: New York City, New York What you’ll be part of Garner is on a mission to transform the U.S. healthcare system — and we’re the only proven player doing exactly that. We partner with employers to redesign how healthcare works: applying 550+ proprietary clinical metrics across 80+ specialties to a dataset of 320M+ patients to identify the best-performing doctors, then using compelling incentives to steer members to the care that helps them get healthier, faster. The result is a rare “win win” — better care and lower costs for both members and employers. In just five years, our work has helped over 2.5 million people access higher-quality care and saved $1B in healthcare costs. We recently raised our Series E and have doubled five years running. If you've ever wanted your work to solve a problem that touches every person in this country, this is the opportunity to do exactly that. You'd be joining a team fundamentally reimagining healthcare in the U.S. — and using AI to scale that impact further and faster than anyone else can. We are seeking an exceptional Senior Marketing Analytics Manager to be embedded in Growth Marketing , the team at Garner that owns B2C member activation & engagement. You will report directly to the Director of Marketing Operations and serve as the dedicated data & analytics partner for our Growth Marketing team. Growth Marketing is responsible for getting employees to sign up and use their Garner benefit — through email, SMS, direct mail, in-app, in-office materials, and employer-led communication channels. We're looking for an exceptional, AI-native data & analytics manager to own how member activation and engagement are operationalized and measured across channels. You'll own the audience targeting & segmentation (SQL queries in Snowflake for our email / sms / direct mail targeting, partnering closely with Engineering) and build the Business Intelligence layer that powers our member engagement campaigns, ranging from cross-system data pipelines, attribution modeling, experimentation frameworks, and funnel & lifecycle analysis through core reporting and dashboards. You'll define the metrics behind member growth and ensure those definitions hold consistently across systems. This is a high-impact role at the heart of our growth engine — helping us engage more members, deliver a first-class member experience, and improve health outcomes at scale. Where you will work: This role will be based in our New York City office (in the Financial District). You must be willing to work in the office 3 days per week on Tuesday, Wednesday and Thursday. What you will do: Targeting & segmentation (campaign operations): Own the audience targeting, segmentation (SQL queries of Snowflake data tables to be built into our Iterable system), and personalization data behind our email, SMS, and direct mail campaigns. Partner with Engineering to troubleshoot upstream Data issues that affect our marketing campaigns, as well as enhance and automate the data mechanics and pipelines so the program can scale. Analytics & Reporting: Own how member activation and engagement are measured end-to-end (e.g., Looker dashboards). Define, build, and maintain the KPIs, metric definitions, performance reports, and dashboards Growth Marketing runs on — funnel and lifecycle metrics, email/SMS campaign activity, channel efficiency, operational health, and KPI target setting. Product & engagement analytics: Bridge marketing activity to member behavior in the Garner app so the team can optimize communications over time. Experimentation: Develop and execute on the Growth Marketing team’s A/B testing program and performance reporting. Data governance: Build our data foundation alongside Data Management & Engineering, Reporting & Business Intelligence, Growth Product to ensure our data is analysis-ready and trustworthy. Build workflows, documentation, QA practices, and tooling that ensure our metrics are standardized across systems and campaigns. Systems & technology stack: Uplevel our data sophistication by designing and building at the systems level, leveraging AI in order to maximize scale and leverage. What you will bring to the team: 4–6+ years in marketing & growth & analytics, business intelligence, growth analytics, marketing analytics, or a similar data-centric role. Growth & marketing, B2C, B2B2C, and Product-led Growth subject matter expertise preferred but not required (e.g., customer funnel analytics, cohort and retention curves, channel attribution, lifecycle email/SMS/direct mail performance, targeting/segmentation, personalization) Expertise in the modern data stack . Hands-on proficiency with Snowflake, SQL, Python, and visualization tools (e.g., Looker, Tableau, Power BI, or similar). Experience with ESP/CRM event data (Iterable, Braze, Salesforce Marketing Cloud, Klaviyo, or similar) is a strong plus. Experience in experimentation & reporting . Familiarity with A/B and incrementality test design, statistics, measurement, and optimization. Analytical rigor and problem framing . You turn a vague business question into the right analysis, define a defensible metric, and state your assumptions rather than jumping to a chart. You’re a strong communicator who’s comfortable using insight to drive decisions for a marketing audience and executives. AI fluency . Comfort with and excitement about harnessing AI agents to build analyses, design dashboards, and validate results. Self-starter approach with the ability to “roll up your sleeves” and juggle multiple priorities & deadlines, doing whatever is necessary to ensure company success. You thrive in a fast-paced, dynamic startup environment. A desire to be a part of a high-performing, mission-driven team that operates with intense urgency, a strong sense of individual accountability, and a commitment to authentic feedback. Please note: we are unable to sponsor or take over sponsorship of an employment visa at this time. What you'll get here: You’ll work on problems that matter, at a company working to change healthcare at scale. You’ll work at the intersection of AI and systemic healthcare reform, where the problems we solve are as interesting and compelling as the mission. At Garner, you’ll take on real, ambitious problems with real ownership and autonomy, alongside exceptional, principles-based people who genuinely want you to win. It’s demanding by design. You’ll be challenged to stretch beyond what you thought possible and receive consistent coaching to help you grow and do the best work of your career. This isn't the right fit for everyone, and that's intentional. The people here are driven by what's at stake for real people, and that's what gives our intensity its purpose. Compensation Transparency: The target salary range for this position is $150,000 - $175,000. Individual compensation for this role will depend on various factors, including qualifications, skills, and applicable laws. In addition to base compensation, this role is eligible to participate in our equity incentive and competitive benefits plans, including but not limited to: flexible PTO, Medical/Dental/Vision plan options, 401(k) with company match, flexible spending accounts, Teladoc Health and more. Fraud and Security Notice: Please be aware of recent job scam attempts. Our recruiters use getgarner.com and garnerhealth.com email domains exclusively. If you have been contacted by someone claiming to be a Garner recruiter or a hiring manager from a different domain about a potential job, please report it to law enforcement here and to candidateprotection@garnerhealth.com . Equal Employment Opportunity: Garner Health is proud to be an Equal Employment Opportunity employer and values diversity in the workplace. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics. Garner Health is committed to providing accommodations for qualified individuals with disabilities in our recruiting process. If you need assistance or an accommodation due to a disability, you may contact us at talent@garnerhealth.com .

Location: London, United Kingdom - Deliveroo Our Global Structure Deliveroo is now part of DoorDash, bringing together teams with even greater reach, scale, and ambition. Depending on your role, you may collaborate with teammates, systems, and leaders across DoorDash and Wolt. Together, we’re unlocking new possibilities as one global team. Join us in our mission to transform the way people shop and eat, where impact, innovation and growth drive everything we do. Our Analytics organisation sits at the heart of Deliveroo powering decision-making across our 3 sided marketplace. We’re looking for an Analytics Engineering Manager to join our London team. This is a hybrid role, with 3 days per week on-site. In this role, you’ll lead a team of Analytics Engineers embedded in a key business domain, owning the pipelines, models and metrics that power day-to-day decisions and building the data foundations your stakeholders rely on. About the Analytics Engineering Org Analytics Engineering is a core pillar of Deliveroo’s Analytics organisation, alongside Data Science. With over 70 Analytics Engineers across the UK and India, we are embedded directly within product and business domains, owning the pipelines, models and metrics that power decision-making at scale: from self-serve AI-enabled analytics and experimentation through to executive reporting and strategic planning. The discipline is evolving fast. With new tooling changing how we work, we are shifting from building data pipelines to building AI first data products, developing rich semantic and data context layers and empowering self-serve data users. This role leads that work across a defined business domain, directly managing a team of Analytics Engineers and helping shape AE standards, culture and direction across the wider org. What You'll Be Doing Directly lead a team of Analytics Engineers embedded in a defined business domain, owning their performance, development and wellbeing Own the AE roadmap for your domain, identifying the highest-leverage investments, prioritising competing requests, and building the case for them with your business and product stakeholders Drive a data products mindset across your estate: clear ownership, SLAs, observability and data contracts built into how your team works by default Maintain strong technical involvement: reviewing data models and SQL, guiding architectural decisions, and stepping in hands-on when your team needs unblocking Contribute to AE-wide decisions on tooling, standards and process, helping shape how Analytics Engineering works at Deliveroo beyond your immediate team Build a high-performing, inclusive team culture by giving regular and actionable feedback, handling performance and motivation challenges, and running effective rituals Partner with Recruiting to hire strong, diverse AE talent into your team What You'll Need to Thrive Essential Experience in an Analytics Engineering, BI Engineering, or Data Engineering role, with strong, hands-on SQL foundations you still draw on regularly Proven experience managing a team of ICs, with a track record of developing people, giving hard feedback, and handling typical team situations independently Demonstrated ability to own a technical roadmap for a domain area and deliver against it with measurable business impact Strong grounding across the modern AE stack (cloud data warehousing, transformation tooling, data modelling, and data quality practices), with the ability to engage credibly on technical decisions and unblock your team Comfortable engaging and influencing at senior business and product level, with experience aligning analytics investment to domain priorities Nice to Have Experience in a marketplace, e-commerce, grocery or retail analytics context Familiarity with semantic and metrics layer tooling, or Python for data automation and pipeline work Exposure to AI for Data, including agentic AI methods, semantic layers, or AI-assisted analytics workflows Experience contributing to analytics ways of working: documentation standards, peer review processes, onboarding, and knowledge sharing Why Join Us? At Deliveroo, you’ll do work that matters, solving real-world problems in a three-sided marketplace that’s constantly evolving. We’re food lovers, problem solvers, community builders and more, brought together by a shared drive to make things better. Working here you can expect to: 🔧 Solve meaningful problems at real scale Work on a complex, always-on marketplace that impacts millions every day. 🌱 See your impact, fast Ship, test and improve ideas quickly in a low-hierarchy, high-ownership environment. 🧠Grow through challenge and ownership Take on big, ambiguous problems and accelerate your career with strong support. 🌎A culture built for builders High standards, collaboration, flexible working and continuous learning. ​​ 💰 Share in the success you help create Competitive salary and equity options, so you’re rewarded for the impact you make. Diversity, Equity and Inclusion At Deliveroo, we know that a great workplace reflects the world around us and that true diversity and inclusion make us stronger, more creative, and better at what we do. We’re committed to fostering an environment where everyone can do their best work and feel they belong. We believe in equality of opportunity and welcome candidates from all backgrounds regardless of age, gender, ethnicity, disability, sexual orientation, gender identity, socio-economic background, religion, or belief. If you have a disability or long-term health condition and need support to apply for one of our roles, or require any reasonable adjustments during the recruitment process, you’ll have the opportunity to let us know once you’ve submitted your application. We’ll share details on how to request support so we can ensure you have a fair and equitable experience. If you’re excited about making a real impact in a fast-moving marketplace and growing your career alongside ambitious, supportive teams, we’d love to hear from you! Beware of recruitment scams: DASH Brands will never ask you to pay money or share sensitive financial information during hiring — learn more about DASH Brands' legitimate recruiting process at careersatdoordash.com/recruitment-scam-awareness .

Location: SF or Remote (US/Canada) At Render, we’re building the modern cloud platform for developers creating AI-native, full-stack, multi-service applications. Our mission is to eliminate the tradeoff between the power of hyperscalers and the simplicity of developer-friendly platforms—so teams can ship fast, scale reliably, and focus on their product, not infrastructure. Unlike complex hyperscalers or ephemeral edge/serverless solutions, Render offers a developer-first experience with persistent compute, dynamic autoscaling, built-in orchestration, and observability, allowing teams to launch, scale, and manage real-world applications without writing infrastructure code or managing servers. Whether you're building LLM-powered applications, scalable SaaS products, or async processing pipelines, Render empowers teams to move fast and scale confidently from MVP to millions of users. Our platform is trusted by over 7 million developers worldwide and continues to grow rapidly. In February 2026, we raised an additional $100M in Series C financing, bringing our total funding to $260M, to accelerate our vision of making cloud infrastructure both powerful and intuitive—designed for the speed of modern AI development. We’re a diverse and talented team that values craft, velocity, and user experience. If you’re excited to help shape the future of the intelligent cloud and empower developers everywhere, we’d love to hear from you. APPLYING TO RENDER We're seeking candidates who possess high integrity, humility, and an insatiable drive to learn. Through reasoned discussions and continuous feedback, we strive to improve both individually and collectively. We foster an environment of mutual trust and respect, empowering effective debate to achieve the best outcomes for our customers and team. We especially encourage members of underrepresented groups in the tech community to apply and understand that not all successful candidates will meet each requirement listed. Our interview process is unique to each role, and we value the candidate experience just as much as our customer experience. We hope your conversations with us reflect a thoughtful process that is illuminative, enjoyable, and respectful of your time. ABOUT THE ROLE We're looking for a Senior/Staff Analytics Engineer to join our growing Data team and lead the evolution of our Analytics Engineering platform. As Render scales, you'll build the foundations that turn raw data into trusted, reusable models for analytics, executive reporting, and AI-assisted decision-making. In this role, you'll partner closely with analysts, scientists, data engineers, and teams across Product, Engineering, Growth, Go-to-Market, Finance, and other business functions. Analysts and scientists will bring domain expertise and own business logic within their areas; you'll own the technical architecture, modeling standards, and engineering practices that help that work scale reliably. As a Senior/Staff-level individual contributor, you'll set the technical direction for Analytics Engineering at Render—strengthening data quality, improving the developer experience, and building semantic and context layers that make data easier to discover and use. You'll help teams move faster with consistent metrics and maintainable models they can trust. WHAT YOU'LL DO - Own our Analytics Engineering architecture. Guide the long-term evolution of Render’s Analytics Engineering platform, strengthening foundational models so our data remains trusted, scalable, and ready for AI-assisted analytics. - Build trusted, reusable data models. Design, build, and maintain governed dbt models that serve as authoritative sources for business-critical metrics across Product, Engineering, Growth, Go-to-Market, Finance, and other teams. - Establish engineering standards. Define and improve practices for data modeling, testing, documentation, version control, CI/CD, and code review. Review high-impact dbt changes and reduce technical debt across the analytics codebase. - Enable self-service and AI-assisted analytics. Design and maintain semantic and context layers that make metrics consistent, data discoverable, and analysis reliable for both people and AI tools. - Partner closely with analysts and scientists. Help analysts and scientists translate domain-specific business logic into scalable, maintainable warehouse models, moving shared logic out of individual reports and dashboards and into governed datasets. - Improve reliability and efficiency. Partner with Data Engineering to strengthen source data quality, warehouse architecture, and BigQuery performance and cost efficiency. - Raise the bar for Analytics Engineering. Mentor analysts, scientists, and analytics engineers on dbt development, dimensional modeling, and engineering best practices, and help teams adopt shared standards. WHAT WE'RE LOOKING FOR - 7+ years of experience in Analytics Engineering, Data Engineering, or a related technical field, including at least 3 years of hands-on experience running dbt in production. - Expert-level SQL skills and a track record of designing and owning scalable Kimball dimensional models. - Deep expertise in modern Analytics Engineering practices, including Git, testing, CI/CD, documentation, data contracts, lineage, and governance. - Experience building semantic and context layers, trusted metrics, and warehouse architectures that support self-service analytics for humans and AI agents across multiple business domains. - Strong understanding of modern cloud data warehouse architecture, performance optimization, and cost efficiency, with experience in platforms such as BigQuery, Databricks, or Snowflake. - A track record of establishing technical standards, influencing engineering practices without formal authority, and improving reliability while reducing technical debt. - Proven ability to partner closely with analysts, scientists, and business stakeholders to translate requirements into scalable, maintainable data models. - Excellent communication skills. You can explain complex technical concepts and tradeoffs to technical and non-technical audiences and build alignment across teams. - Experience building data models that connect product usage, acquisition, CRM, and financial data across the customer lifecycle. - Experience using AI-assisted coding or analytics tools such as Codex, Cursor, or Claude Code to accelerate data modeling, testing, documentation, or exploration. NICE-TO-HAVES - Hands-on experience with Render’s analytics stack, including BigQuery, Segment, dbt, and analytics tools such as Metabase or Mixpanel. - Experience with developer-focused, product-led, sales-led, or usage-based businesses. - Knowledge of cloud infrastructure, PaaS, developer tooling, or other technically complex products. If this role excites you but you don’t meet every single requirement, we’d still love to hear from you—your unique experience might be just what we need. BENEFITS - 4 weeks of paid vacation. - 14 weeks of fully paid parental leave for all parents to bond with a newly born, adopted, or fostered child. We will also work with you to create a supportive plan of return. - Long-term disability, life insurance, and 401K plans. - 100% employer-paid medical coverage and 99% employer-paid dental and vision coverage for you and a dependent. FSAs and HSAs are available as well. - Monthly lifestyle stipend for wellness, mental health and therapy, hobbies, etc. - Monthly cell phone and internet subsidy. - Commuter benefits for Renders in the Bay Area, and home office stipends for remote Renders. - Continuous learning benefits & related support. This position is generally not eligible for new visa sponsorship. At Render's discretion, the business may sponsor existing visa transfers. Applicants who require sponsorship must receive business authorization. Render is an equal-opportunity employer. We know that employing a team rich in diverse thoughts, experiences, and opinions allows our employees, product, and community to flourish. We make all employment decisions including hiring, evaluation, termination, promotional, and training opportunities, without regard to race, religion, color, sex, age, national origin, ancestry, sexual orientation, physical handicap, mental disability, medical condition, disability, gender or identity or expression, pregnancy or pregnancy-related condition, marital status, height and/or weight. 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. We encourage all who are interested to apply. We can't wait to hear from you! 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Задачи: — Превращать данные в более умные продуктовые решения на международных цифровых проектах. Требования: — 3–5 лет опыта в аналитике данных, продукта, веба или приложений. — Отличное знание SQL. — Опыт работы с Google Analytics 4 и веб/мобильным трекингом. — Знание ETL процессов и построения дата пайплайнов. — Владение Power BI, Tableau, Looker Studio, Qlik или SAP BusinessObjects. — Знания в области статистики, экспериментов и A/B тестирования. — Английский язык на уровне B2 и выше. Будет плюсом: — Опыт работы с BigQuery. — Опыт серверного трекинга. — Опыт в e-commerce. Условия: — Работа в международной команде. — Гибридный формат работы в Ташкенте. — Полная занятость. — Зарплата от 2500 USD net в месяц.

Задачи: — Ведение HR-аналитики, подготовка регулярной отчетности по персоналу — Анализ HR-показателей (текучесть, укомплектованность, вовлеченность) — Автоматизация HR-процессов, работа с AI-инструментами (ChatGPT, Copilot) для отчетности и аналитики — Организация опросов сотрудников, участие в HR-проектах — Координация программы медицинского страхования Требования: — Высшее образование: HR / Экономика / Финансы / Менеджмент — Продвинутый Excel и PowerPoint — обязательно (сводные таблицы, формулы, анализ данных) — Английский язык — не ниже Upper-Intermediate — Опыт ведения HR-проектов — Плюсом будет: опыт с ERP (SAP SuccessFactors, 1С, Oracle HCM) и Power BI Условия: • Официальное трудоустройство • Ежегодное повышение зарплаты • Медстраховка сотрудника и семьи • Питание (комплексный обед) • Развозка утром и вечером корпоративным транспортом • Корпоративное обучение • Испытательный срок — 3 месяца • Возможности карьерного роста

Uzum — это экосистема цифровых сервисов для развития бизнеса, онлайн-шопинга, удобных платежей и решения других бытовых задач в Узбекистане. Компания оценивается в $1,5B+, размер команды — 1000+. Требования: — Опыт управления командой — Опыт отслеживания эффективности складских операций — Опыт снижения потерь и брака в маркетплейсе Вакансия предполагает работу в формате remote или в офисе в Ташкенте.