Вакансии

Задачи: — Build PoCs with the team, then take the proven ones to production or write the spec for the team that will run them. — Solve real problems, finding the pain points, design the fix, ship it and prove the value. — Design for scale where every PoC fits our wider IT landscape and Enterprise Architecture. — Own the architecture that lets AutoStore build AI solutions safely across the company. — Work with the IT teams already building our foundations (data, integration, security, authentication and hosting). — Define what AI needs from them and build on top of what they deliver. — Bring people along by explaining choices and trade-offs in plain language, to developers and business leaders alike. Требования: — Experienced builder with full-stack developer background. — Comfortable writing code for a prototype as well as making architecture decisions. — Knowledge of how data, integration, security and hosting fit together in a large organization. — Nice to have: experience with Azure, Databricks, or taking AI solutions into production. Условия: — Relocation to Norway (Oslo, Stavanger, or Nedre Vats). — Collaborative and inclusive culture valuing diverse perspectives. — Work-life balance with 1 hour per week of paid exercise, health insurance, and a generous pension plan. — Creative and safe workplace in Norway’s first unicorn listed on the Oslo Stock Exchange. — International and supportive environment within a Norwegian multinational. Как мы работаем: — Think big, start small, move fast. — Prototype in weeks, not months. — Build, test, kill, build again. — Build on Azure Databricks data platform following IT and enterprise architecture for scalability. — Proven ideas move to production or handover to operational teams. — Share learnings across the company as we scale up.

Location: Dallas, USA; New York, USA; Orlando, USA We are looking for a hands-on Lead Python Engineer / Technical Architect to act as the senior technical member of a small engineering team. The role combines Python development, AWS architecture, technical leadership, and direct collaboration with business stakeholders. The successful candidate will design and implement scalable solutions, modernize existing applications, establish engineering standards, and mentor junior and mid-level developers. The successful candidate will be able to move effectively between business discussions, solution design, architecture, development, code review, and mentoring, applying pragmatic technical leadership and excellent stakeholder communication to transform business-developed applications into robust, scalable, and maintainable engineering solutions. This is not a purely architectural or managerial role. The successful candidate is expected to remain actively involved in solution design, coding, code reviews, and delivery. This is a hybrid position requiring onsite presence at the client’s Chicago office 3 days per week. The estimated salary range for this position is $190,000 to $210,000 per year. Lead solution architecture and technical design activities Design, develop, and maintain production grade Python applications Refactor and modernize applications originally developed by business teams Design scalable, resilient, secure, and observable AWS native solutions Contribute to data architecture and solutions based on modern cloud data platforms (Snowflake preferred) Define engineering standards, design patterns, testing practices, and CI/CD processes Conduct code reviews and support software quality, maintainability, and security Collaborate with business stakeholders and subject matter experts to translate business needs into technical solutions Work effectively in an environment with limited Business Analyst support Mentor junior and middle level engineers and facilitate knowledge transfer across the team Strong hands on Python development experience Proven experience designing and building production grade applications Strong AWS architecture and cloud engineering expertise Previous experience as a Technical Lead, Lead Engineer, or hands on Architect Experience modernizing or refactoring legacy or business developed applications Strong SQL skills Knowledge of software architecture and design patterns Knowledge of API design and system integration Knowledge of automated testing and quality engineering Knowledge of CI/CD and version control Knowledge of application security, monitoring, and observability Experience with modern cloud data platforms (e.g. Snowflake, Redshift, Databricks, BigQuery) Experience working with data intensive applications or analytics solutions Strong stakeholder communication and requirements analysis skills Experience mentoring and supporting junior and middle level engineers Ability and willingness to work onsite in Chicago 2-3 days per week Experience in Financial Services, particularly Asset Management, Investment Management, or Capital Markets Experience with portfolio management, investment analytics, Fixed Income, or ETF solutions Hands on Snowflake experience Exposure to Aladdin, BNY, or comparable financial platforms and integrations Experience modernizing applications developed by business analyst or quantitative teams Familiarity with AI enabled software development, agentic workflows, or AI assisted SDLC

Location: United States, Austin, TX 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. Data Engineer PlayStation's Infrastructure Business Operations team is looking for a Data Engineer to build the data foundation for understanding the cost, utilization, and economics of PlayStation’s global infrastructure. Our infrastructure spans data centers, compute, storage, networking, Kubernetes, public cloud, SaaS, and other technology services. You will work alongside our engineering, product, finance, FinOps, and operations teams to build a data platform that can connect these disparate data sources into a trusted view of how our infrastructure is used, what it costs, and ultimately how those costs contribute to the economics of our products. You will own the end-to-end implementation, starting with identifying the questions that matter, determining the data required to answer them, building the pipelines and models to make that data reliable and accessible, and finally turning it into insights that drive better decisions. What You’ll Do Build scalable data pipelines that ingest, transform, and combine physical infrastructure, engineering system, financial, and product data. Develop cost and allocation models that connect infrastructure consumption to workloads, services, features, and products. Partner with engineering teams to understand complex infrastructure and identify the telemetry and instrumentation needed to measure it. Analyze infrastructure cost, utilization, capacity, and unit economics to help drive key business decisions across all our teams. Create trusted metrics, datasets, dashboards, and analytical tools used by engineering, product, Finance, and leadership. Establish strong practices around data quality, testing, observability, documentation, and reproducibility. Explore new data sources and technologies that improve how we understand and operate our infrastructure. What We’re Looking For 3+ years in a similar role, focused on building production data pipelines, data models, and analytical systems. Advanced SQL skills and proficiency with Python or similar data-oriented programming languages. Experience with modern data platforms and tooling such as Snowflake, Databricks, dbt, and automated ETL/ELT pipelines. Strong analytical skills—you’re comfortable investigating the data yourself, challenging results, and translating findings into clear conclusions. Experience working with large, complex datasets across multiple systems and levels of granularity. Ability to translate ambiguous business and technical problems into measurable requirements and scalable data solutions. Experience and flexibility with current analytics and visualization tools. Familiarity with teams and engineering systems that utilize both on-prem and cloud infrastructure. Strong communication skills and the ability to work across global engineering, product, Finance, and business teams. Nice to Have Bachelor’s degree in computer science Experience with AWS, Google Cloud, or Azure billing and usage data. Experience with Kubernetes telemetry, networking, or data center operational data. Familiarity with infrastructure cost allocation, unit economics, capacity planning, forecasting, or FinOps. Experience connecting technical infrastructure consumption to product or business metrics. PlayStation isn't just the Best Place to Play - it's also the Best Place to Work. We've thrilled gamers since 1994 when we launched the original PlayStation. Today, we're recognized as a global leader in interactive and digital entertainment. The PlayStation brand falls under Sony Interactive Entertainment, a wholly owned subsidiary of Sony Corporation. Sony is an Equal Opportunity Employer. All persons will receive consideration for employment without regard to race, color, religion, gender, pregnancy, national origin, ancestry, citizenship, age, legally protected physical or mental disability, covered veteran status, status in the U.S. uniformed services, sexual orientation, marital status, genetic information 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. We sincerely appreciate the time and effort you spent in contacting us and we thank you for your interest in PlayStation. 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 (where applicable) 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: — Разработка и вывод в продакшн data-приложений на Python/Streamlit в Databricks Apps — Доработка Lineage Explorer до полной готовности к продакшну — Проектирование нового приложения для ввода и показа данных (до ~600 пользователей) — Проактивные предложения по UX и архитектуре Требования: — Кандидаты только из ЕС Условия: — Проект для заказчика из Дании, длительность 3 месяца, старт 28.10.2026.

Location: USA 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. Solvd Cloud, Infra, Data & Security is growing fast, and our architecture leadership needs to keep up. We need someone who can take an unclear problem, define it, design the answer, and make sure it ships. You'll set technical direction across cloud, infrastructure, and data. You'll shape engagements and roadmaps before they're committed. And you'll stay close enough to delivery that what we design is what gets built. We operate AI-first: you'll use AI as a daily tool to move faster and multiply what you and the teams around you can deliver. There will be ambiguity. That's the job. The plans don't exist yet, and you'll help write them. WHY THIS ROLE, WHY NOW: - You'll help define the business, not inherit it. The Cloud BU is rapidly scaling. The patterns, standards, and team habits you set now become how we operate. - The scope is broad on purpose. It covers cloud foundations, Kubernetes platforms, data, and AI workloads, so you won't be boxed into one layer. - Decisions move quickly. You'll work directly with BU leadership, and decisions take days, not quarters. - The problems are current. The work is getting AI workloads into production safely, building data platforms that are governed, and keeping cloud spend under control. WHAT YOU'LL OWN: - Architecture direction. You'll define reference architectures, landing zones, and standards across AWS and Azure, Kubernetes, and infrastructure-as-code. You'll decide what we standardize and what we leave flexible. - Data and AI platforms. You'll design lakehouse and warehouse, streaming, and governance patterns. You'll also design the platform layer that moves GenAI and agentic workloads from prototype to production, covering access control, evaluation, observability, and cost guardrails. - Solution shaping. You'll lead technical discovery, size and de-risk the work, and write the solution designs and technical scope that teams commit to. - AI-accelerated delivery. You'll use AI tools across the architecture lifecycle: discovery synthesis, design drafts, IaC and code generation, review, documentation, and estimation. You'll turn what works into repeatable patterns and prompts the team adopts. You'll also set the guardrails for how AI is used with client and production data. - Security and compliance by design. You'll own IAM, network segmentation, secrets management, and logging. Your designs need to hold up to SOC 2, ISO 27001, and regulated-industry scrutiny without slowing delivery down. - Cost and operability. Every design ships with a run cost, reliability targets, an observability plan, and a rollback path. - Raising the bar. You'll run design reviews, mentor architects and senior engineers, and turn repeat solutions into reusable accelerators. WHAT YOU BRING: Have 12+ years in infrastructure, cloud, or data engineering, including several years as the accountable architect for production systems at scale. Have deep hands-on experience with AWS and/or Azure, production Kubernetes, and Terraform (or an equivalent IaC tool). You can still review a pull request credibly. - Have designed and shipped modern data platforms, such as [Databricks / Snowflake / Fabric / Redshift], including governance and data quality, not just pipelines. - Think security-first. IAM design, zero-trust networking, encryption, and audit readiness are defaults for you, not afterthoughts. - Use AI as a force multiplier, not a novelty. You can show concrete examples of AI shortening your delivery timelines or expanding your output. You also know where it fails, and you verify what it produces before anything reaches production. - Can explain a tradeoff to a CFO in the morning and debug it with an engineer in the afternoon. - Act under ambiguity. You write the first draft of the plan instead of waiting to be handed one, then adjust it as you learn. NICE TO HAVE - You've put GenAI or LLM systems into production (RAG, evaluation, guardrails, agent orchestration). - You have multi-cloud or hybrid experience at enterprise scale. - You've worked in regulated industries such as financial services, healthcare, or the public sector. - You hold AWS Solutions Architect Professional, Azure Solutions Architect Expert, or CKA. These help but aren't required. - You've built an architecture practice or center of excellence from an early stage. 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.

Location: São Paulo, Brazil Why Join Exadel We’re an AI-first global tech company with 25+ years of engineering leadership, 2,000+ team members, and 500+ active projects powering Fortune 500 clients, including HBO, Microsoft, Google, and Starbucks. From AI platforms to digital transformation, we partner with enterprise leaders to build what’s next. What powers it all? Our people are ambitious, collaborative, and constantly evolving. About the Client Our customer is a leading financial technology company in Brazil, operating at the intersection of Finance, Technology, and Data. The company leverages technology and data-driven solutions to build scalable financial operations and improve decision-making across the organization. What You’ll Do Partner with Finance teams to understand business processes, rules, requirements, and operational needs, translating them into scalable data solutions. Develop SQL queries, analyses, notebooks, dashboards, and automations to support Finance activities and decision-making. Build and maintain data pipelines, transformation processes, and validation routines, ensuring reliable and traceable data. Support critical Finance processes, including financial close, reconciliations, controls, and regulatory reporting. Investigate data inconsistencies, identify root causes, and implement solutions to improve data reliability and process efficiency. Implement data quality, monitoring, governance, and traceability controls. Document business rules, workflows, processes, and technical solutions to ensure knowledge is clearly maintained and shared. Collaborate closely with Finance, Engineering, Product, Data, Risk, and Audit teams. Manage priorities and drive deliveries end-to-end, from understanding the business need through implementation and continuous improvement. What You Bring Strong hands-on experience with SQL, combined with practical experience in data analysis, transformation, and validation. Knowledge of Python or another programming language, with the ability to develop analytical solutions and automate processes. Experience working with ETL/ELT pipelines, data integration, and data processing, as well as notebooks, dashboards, or BI tools. Strong ability to translate business rules and financial or operational requirements into technical logic and data solutions. Understanding of data quality, governance, security, and traceability principles. Familiarity with financial, accounting, or operational processes and the ability to collaborate effectively with both technical and business stakeholders. Strong analytical, problem-solving, communication, and stakeholder management skills. Nice to have Experience in Controllership, Accounting, FP&A, Tax, Treasury, or Regulatory Reporting. Knowledge of IFRS, financial close processes, and regulatory reporting. Experience with Databricks, Apache Spark, cloud platforms, APIs, or data lakes. Knowledge of ERP systems, general ledgers, or subledgers. Experience working in regulated and audit-driven environments. Familiarity with automated testing, CI/CD, and data pipeline monitoring. English level Intermediate/Upper-Intermediate Work Type: Hybrid Location: São Paulo, Brazil Legal & Hiring Information Exadel is proud to be an Equal Opportunity Employer committed to inclusion across minority, gender identity, sexual orientation, disability, age, and more Reasonable accommodations are available to enable individuals with disabilities to perform essential functions Please note: this job description is not exhaustive. Duties and responsibilities may evolve based on business needs Compensation details are shared with candidates at the early stage of the recruitment process. The offer is not binding until a signed contract is in place. Your Benefits at Exadel Exadel benefits vary by location and contract type. Your recruiter will fill you in on the details. International projects In-office, hybrid, or remote flexibility Medical healthcare Recognition program Ongoing learning & reimbursement Well-being program Team events & local benefits Sports compensation Referral bonuses Top-tier equipment provision Exadel Culture We lead with trust, respect, and purpose. We believe in open dialogue, creative freedom, and mentorship that helps you grow, lead, and make a real difference. Ours is a culture where ideas are challenged, voices are heard, and your impact matters.

Задачи: — Разрабатывать и развивать пайплайны данных и платформенный слой, от которого зависят AI-продукты компании; — Анализировать использование LLM: стоимость, экономику токенов и кеширования, финансовую отчетность по расходам на AI; — Развивать RAG-системы: контекстные базы знаний, инфраструктуру векторного и семантического поиска; — Обеспечивать эксплуатационную надежность платформы: профилирование, мониторинг и observability пайплайнов, за которые вы отвечаете; — Разрабатывать интерфейсы и сервисы поверх данных, а не только обеспечивать их загрузку: авторизацию, API и интерактивный доступ для пользователей данных. Требования: — Сильный коммерческий опыт в Data Engineering с современным стеком: Databricks, dbt, Airflow, Dagster, Greenplum, Snowflake, или аналогичными технологиями; — Уверенное владение Python и понимание backend-разработки: как работает авторизация, как сервис предоставляется пользователям и как с ним взаимодействуют; — Практическое понимание профилирования и мониторинга data-систем в production; — Глубокое понимание AI/LLM-стека: векторных баз данных, embeddings, контекстного и семантического поиска, RAG-архитектур и принципов работы автономных агентов; — Опыт работы с облачными технологиями, в идеале — AWS. Условия: — Гибкий график и удалённый формат работы; — ДМС для сотрудников, их партнеров и детей, компенсация онлайн-сессий с психологом и занятий спортом; — Оплата участия в профильных конференциях и курсах, внутренние конференции; — Компенсация изучения иностранного языка; — Регулярные офлайн-ивенты и корпоративные мероприятия.

Core Requirements: — Strong experience with Databricks and Lakehouse medallion architecture (bronze / silver / gold) — Advanced PySpark skills for building transformations in notebooks — Hands-on experience with Delta Lake — Experience with Data Vault modelling (hubs, links, satellites) — Experience with dimensional modelling (facts and dimensions) — Experience ingesting data with Fivetran and custom API integrations — Experience working with Oracle SQL databases as source systems — Spark performance tuning, including skew handling and Liquid Clustering — Experience deploying with Databricks Asset Bundles (DABs) — Experience with Unity Catalog, group-based RBAC, and PII masking Nice to Have: — Experience with Great Expectations or similar data quality frameworks — Experience handling unstructured files in Blob storage — Experience supporting LLM / agent and ML use cases with curated data What You'll Work On: — Building and maintaining a Databricks Lakehouse on a medallion architecture — Ingesting data from Oracle systems and APIs into the bronze layer — Modelling the silver layer with Data Vault and the gold layer with dimensional models — Optimising Spark performance and Delta table layouts — Implementing governance, access control, and PII masking in Unity Catalog — Replacing manual scheduling processes and spreadsheets with a unified data platform — Collaborating with the application team that builds on top of the gold layer for the web app, LLMs, and ML models

Задачи: — Сотрудничество с командами продаж и инженерии для ускорения внедрения и роста платформы Databricks у клиентов. — Обеспечение успеха клиентов через техническое руководство и поддержку наиболее сложных клиентов. — Ведение технической стратегии и плана исполнения для ключевых клиентов и кейсов использования. — Быть основным техническим контактом по вопросам статуса производства и запуска кейсов использования. — Координация с внутренними и внешними командами, включая профессиональные сервисы и продуктовые команды. — Разработка и выполнение плана действий, охватывающего все технические роли и команды, взаимодействующие с клиентом. Требования: — Опыт 5+ лет в технической реализации проектов/программ в области данных и ИИ. — Навыки программирования на Python, SQL или Scala. — Опыт работы с клиентами в предподажной, технической архитектуре, успехе клиентов или консалтинге. — Понимание архитектуры распределённых систем данных. — Умение связывать бизнес-ценность с результатами проектов. — Опыт управления программами, включая управление аккаунтами, заинтересованными сторонами и ресурсами. — Опыт решения сложных эскалаций с руководителями клиентов. — Навыки проведения стратегических сессий, бизнес-анализа и управления сложными проектами. — Высшее образование в области компьютерных наук, информационных систем, инженерии или эквивалентный опыт. — Готовность к командировкам до 30%. Условия: — Гибридный формат работы. — Годовой оклад от $180,000 до $247,500 USD. — Возможность получения бонусов, акций и других льгот. — Компания придерживается принципов равной оплаты и инклюзивности. — Дополнительная информация о льготах доступна по ссылке в вакансии.

Location: Bengaluru, Karnataka, India, APAC From Fivetran’s founding until now, our mission has remained the same: to make access to data as simple and reliable as electricity. With Fivetran, customer data arrives in their warehouses, canonical and ready to query, with no engineering or maintenance required. We’re proud that more organizations continue to leverage our technology every day to become truly data-driven. About Us Fivetran and dbt Labs are bringing together two industry-leading companies with a shared mission: helping organizations unlock the full value of their data. Together, we’re delivering the data infrastructure layer that helps organizations move, transform, and trust their data — from the moment data moves, through every transformation, to the context teams and AI systems rely on. Fivetran helps organizations automate data movement across the systems, clouds, engines, and tools they rely on. dbt Labs pioneered analytics engineering, helping teams transform data into reliable, governed insights. Together, we support thousands of organizations as they build a trusted foundation for analytics, AI, and better business decisions. As we bring our teams and technology together, we’re building on the strengths of both companies while continuing to deliver the products and experiences our customers know and trust. It’s an exciting time to join us: we’re creating a company with the scale, talent, and technology to help more organizations put their data to work with greater speed, confidence, and impact. During this transition period, you may see references to both Fivetran and dbt Labs throughout our recruiting process as we integrate our teams, systems, and career sites. About the Team The Semantic Layer team owns the systems that turn dbt models into trusted, reusable business metrics. At the heart of this is MetricFlow — the open-source semantic engine that powers the dbt Semantic Layer. MetricFlow lets data teams define metrics once in code and consume them consistently across BI tools, notebooks, AI agents, and downstream applications. This team is the steward of MetricFlow as an open-source project: shipping releases, reviewing community contributions, evolving the query compiler, and ensuring it integrates cleanly with the broader dbt ecosystem. You'll work at the intersection of language design, query compilation, and distributed data execution — solving problems that directly shape how thousands of organizations measure their business. About the Role We're hiring a Senior Software Engineer to join the Semantic Layer team in Bangalore. You'll be a core contributor to MetricFlow — designing features, optimizing query generation, hardening the open-source codebase, and partnering with the community of contributors and adopters around it. This is a high-ownership role: you'll write production code, drive technical decisions, and help shape the long-term architecture of one of the most important projects in the modern data stack. What You'll Do Design, build, and maintain core features of MetricFlow, including metric definitions, query compilation, dimensional modeling, and SQL generation across multiple data warehouses (Snowflake, BigQuery, Databricks, Redshift, and others). Own MetricFlow as an open-source project — triage issues, review external pull requests, manage releases, and engage the community on GitHub and in Slack. Collaborate with engineers across dbt Cloud, dbt Core, and the Semantic Layer service to ensure MetricFlow integrates seamlessly with the rest of the dbt ecosystem. Improve performance, reliability, and observability of metric query execution at scale. Partner with product, design, and developer-relations teammates to translate customer and community feedback into shipped improvements. Write clear technical documentation, RFCs, and design docs that raise the bar for how the team thinks and ships. Mentor other engineers through code review, pairing, and technical guidance. Skills We're Looking For Strong professional software engineering experience, with a strong track record of shipping production systems. Deep proficiency in Python , including modern typing, testing practices, and packaging. Strong SQL fundamentals and a working understanding of how analytical query engines and data warehouses execute queries. Experience designing systems that involve parsing, compilation, or transformation — for example: query planners, DSL compilers, type systems, or rule-based engines. Solid grasp of software design principles: clean APIs, modularity, testability, and backwards compatibility. Excellent written and verbal communication — you can explain complex tradeoffs clearly to engineers, PMs, and external community members. Experience collaborating in a distributed, asynchronous team environment. Bonus Skills (Optional) Prior experience contributing to or maintaining a popular open-source project. Familiarity with dbt, MetricFlow, LookML, Cube, or other semantic-layer technologies. Background in data warehousing internals, query optimization, or analytical SQL dialects. Experience with CI/CD, GitHub Actions, and release engineering for Python libraries. Exposure to building developer-facing APIs, SDKs, or CLIs. Why Join Us Impact at scale: Your code will run inside the data platforms of tens of thousands of companies, including some of the world's largest enterprises. Open-source ownership: You'll be a public, named maintainer of a foundational project — your work is visible, reviewed, and used by the global data community. A team that values craft: We invest in design docs, code review, and durable engineering. We ship fast, but we don't ship sloppy. Competitive compensation: Market-leading salary, equity, comprehensive health insurance, generous time off, learning & wellness stipends, and home-office support. Perks and Benefits 100% employer-paid medical insurance * Generous paid time away from work, including paid vacation or flexible/unlimited vacation depending on role and country, plus paid sick time, inclusive parental leave, paid holidays, including a year-end Global Week of Rest, and volunteer days off. RSU stock grants* Professional development and training opportunities Company virtual happy hours, free food, and fun team-building activities Monthly cell phone stipend Access to an innovative mental health support platform that offers personalized care and resources in areas such as: therapy, coaching, and self-guided mindfulness exercises for all covered employees and their covered dependents. * May vary by country and worker type - please reach out to your recruiter for more information Click here to learn more about Fivetran's Benefits by Region. We’re honored to be valued at over $5.6 billion , but more importantly, we’re proud of our core values of Get Stuck In, Do the Right Thing, and One Team, One Dream . Read about us in Forbes . Fivetran brings together high-quality talent across the globe to make data access as easy and reliable as electricity for our customers. We value and recognize that our customers benefit from having innovative teams made of people from many backgrounds, experiences, and identities. Fivetran promotes diversity, equity, inclusion & belonging through attracting, recruiting, developing, and retaining a diverse workforce, not only because it is the right thing to do, but because it helps us build a world-class company to better serve our customers, our people and our communities. To learn more about Fivetran’s culture and what it’s like to be part of the team, click here and enjoy our video. To learn more about our candidate privacy policy, you can read our statement here . We are committed to ensuring that all candidates have an equal opportunity to participate in our interview process. If you require accommodations at any stage of the process due to a disability, medical condition, or any other circumstance, please don't hesitate to submit your request by filling out this form . We will work with you to provide reasonable accommodations to facilitate your participation and ensure a fair and accessible interview experience. Your request and any information provided will be kept confidential and will not impact your candidacy. We look forward to hearing from you and accommodating your needs to the best of our ability.

Задачи: – Обеспечить сквозную доставку одного или нескольких приоритетных доменов данных в Azure Databricks. – Разработка и создание конвейеров обработки данных уровня Medallion (Bronze/Silver/Gold) с использованием декларативных конвейеров Lakeflow, Auto Loader, Structured Streaming и Delta Lake с кластеризацией Liquid. – Зарегистрировать отобранные данные в каталоге Unity с указанием правильных тегов, масок, фильтров строк, происхождения и политик доступа. – Внедрить контрольные точки качества данных на границе между «серебряным» и «золотым» уровнями и уточнить правила совместно с экспертами в данной области. – Упаковка и развертывание проектов с использованием Databricks Asset Bundles через Azure DevOps CI/CD. – Разрабатывать автоматизированные тесты и документацию. – Начать работать на уровне ИИ как соавтора уже сегодня, а затем перейти к ИИ как оркестратору, используя Claude Code, Databricks Assistant, GitHub Copilot и инструменты агента, подключенные к MCP, для ускорения повторяющихся этапов сборки, тестирования и развертывания конвейера. Требования: – Более 6 лет опыта работы в области проектирования данных, из которых как минимум последние три года — с использованием Databricks в производственной среде. – Обширный практический опыт работы с архитектурой Medallion/Lakehouse, Delta Lake, Unity Catalog, декларативными конвейерами Lakeflow и пакетами ресурсов Databricks. – Уверенное владение Python, PySpark и SQL, умение диагностировать проблемы производительности в больших рабочих нагрузках с помощью Spark UI и Photon. – Реальный опыт работы в производственной среде с потоковой обработкой данных (Kafka Structured Streaming, Auto Loader) и использованием алгоритмов CDC. – Опыт внедрения систем обеспечения качества данных в масштабах предприятия (Great Expectations или аналогичные), а также опыт в области отслеживания происхождения данных, каталогизации и контроля доступа. – CI/CD на платформах данных с использованием Azure DevOps или GitHub Actions, с инфраструктурой как кодом (Terraform или аналогичные решения). – Свободное владение рабочим английским языком.

О компании: Salmon — технологическая финансовая компания, строящая банковскую и кредитную платформу в Юго-Восточной Азии, начиная с Филиппин. За три года компания достигла более 7 млн загрузок приложения, 2 млн активных пользователей в месяц, 7000+ партнерских магазинов и привлекла более 350 млн долларов от ведущих инвесторов. Задачи: — Владение слоем данных для функции Collections: создание моделей, отчетов и наборов данных, необходимых для принятия решений и отслеживания показателей. — Работа на стыке Collections, Risk и DWH: построение и поддержка аналитической инфраструктуры, связывающей сырые данные с операционными решениями. — Разработка и поддержка регулярных отчетов и дашбордов по ключевым метрикам Collections, обеспечение их точности, документации и полезности. — Мониторинг качества данных, самостоятельное расследование и устранение несоответствий до того, как они повлияют на решения. — Создание и поддержка моделей данных и аналитических наборов данных для операций и отчетности Collections. — Разработка новых отчетов и дашбордов, поддержка запросов ad-hoc анализа от Collections и смежных функций. — Исследование проблем с качеством данных, выявление коренных причин и четкая документация результатов. — Документирование логики расчетов, источников данных, наборов данных и отчетов для упрощения работы последующих сотрудников. Требования: — Опыт 1–2+ года в аналитике данных, продукта, риска или операционной аналитике. — Сильные навыки SQL и практический опыт работы с большими наборами данных. — Опыт построения и поддержки моделей данных и регулярной отчетности. — Твердое понимание принципов качества данных, способность самостоятельно выявлять коренные причины несоответствий. — Готовность к релокации в Манилу — значительное преимущество. Желательно: — Опыт работы с Databricks или аналогичными инструментами. — Опыт работы с dbt или аналогичными фреймворками трансформации данных. — Опыт создания дашбордов в Tableau или аналогичных BI-инструментах. — Опыт работы с финансовыми или кредитными данными, особенно в Collections или Risk. Условия: — Гибридный формат работы. — Основные часы работы: 12:00–19:00 по манильскому времени (UTC+8). — 22 дня отпуска + государственные праздники Филиппин + 15 дней больничных. — Медицинская страховка для сотрудника и семьи с первого дня. — Доступ к внутреннему психологу. — Офис в Bonifacio Global City (BGC), Манила. — Поддержка релокации: перелеты и двухнедельное проживание для сотрудника, семьи и питомцев. — Оформление визы, документов и логистика под контролем компании. — $2,500 в год на перелеты домой. — Регулярные выездные мероприятия, спорт и командные события по Юго-Восточной Азии. — Лучшие команды получают неделю в пляжном доме в регионе SEA.

Location: San Francisco; New York City Workplace: Hybrid Perplexity is AI for people who expect more. On the data team, that means building the systems that make our data reliable, understandable, and usable by both humans and AI. We're looking for an analytics engineer or data engineer who wants to build the foundation for an AI-native data organization. You'll design core data models, pipelines, semantic layers, data quality systems, governance practices, and warehouse workflows that power the entire company: helping teams make strategic decisions, operate the business, and move faster with trusted data. You'll also make sure those systems are secure, privacy-aware, and legible to AI agents, data scientists, and the rest of the company. This role is for someone who can operate at the boundary of analytics engineering, data engineering, data governance, and internal product. You care about dimensional modeling, dbt standards, cost-aware warehouse design, access controls, privacy, and the details that make data trustworthy. You also believe AI should make the data stack faster, easier to maintain, and more accessible across the company without weakening security or governance. WHAT YOU'LL DO - Build the core data foundation - design and maintain high-quality data models, marts, and pipelines that make analysis fast, reliable, and reusable. - Manage the data warehouse - help own warehouse architecture, environments, permissions, performance, cost, data lifecycle, and operational hygiene so the platform scales cleanly. - Make the warehouse AI-readable - own the documentation, semantic context, metadata, lineage, and retrieval patterns that AI systems depend on to understand and query Perplexity's data correctly. - Own data modeling standards - define and champion dbt patterns, dimensional modeling practices, naming conventions, tests, and review processes. - Lead data governance practices - define standards for access, ownership, lineage, documentation, retention, quality, and sensitive data handling across the analytical warehouse. - Build with security and privacy in mind - partner with engineering, security, legal, and finance where needed to ensure data access, sharing, and AI-enabled workflows are appropriate and controlled. - Automate data quality and maintenance - build AI-assisted workflows that detect issues, explain root causes, suggest fixes, generate tests, and reduce manual firefighting. - Improve data team productivity - automate repetitive workflows, improve tooling, streamline development, and make it easier for data scientists and stakeholders to answer questions. - Partner across the company - work closely with data scientists, engineering, product, finance, and GTM teams to translate analytical needs into durable data systems. - Shape tooling decisions - evaluate build-versus-buy tradeoffs, manage vendor relationships when needed, and choose tools that scale with the team. WHAT WE'RE LOOKING FOR - 6+ years of experience as an analytics engineer, data engineer, data scientist, or closely related role. - Deep SQL expertise - you can reason about correctness, performance, joins, grain, and edge cases in complex warehouse queries. - Strong data modeling experience - you've worked hands-on with dbt (or a similar transformation framework) in production, and you understand dimensional modeling, data contracts, testing, and how analytical schemas should evolve. - Pipeline ownership - you've built, maintained, debugged, and improved production data pipelines. - Warehouse management experience - you've worked with warehouse administration, access patterns, permissions, performance tuning, cost management, or operational ownership. - Governance mindset - you think clearly about data ownership, access controls, privacy, retention, lineage, auditability, and the risks of making data too easy to access. - AI-native working style - you already use AI to speed up development, documentation, QA, exploration, and repetitive workflow automation. - Stakeholder fluency - you know how to turn messy analytical requirements into trusted models, metrics, and reusable data assets. - Autonomy and execution - you can take projects from ambiguous problem to production-quality system with minimal oversight. - Operational judgment - you care about reliability, governance, security, cost, and long-term maintainability. BONUS - Snowflake administration, optimization, cost management, or warehouse performance tuning. - Experience with RBAC, PII handling, data classification, retention policies, audit workflows, or privacy/security reviews. - Experience with Databricks or other modern data infrastructure. - Experience building semantic layers, metrics layers, metadata systems, or data catalogs. - Python experience for data tooling, automation, orchestration, or quality checks. - Previous experience as an early analytics engineer or data engineer at a high-growth startup. WHY THIS ROLE - Own the foundation - your work will determine how fast and confidently the company can use data. - Build for humans and AI - the next generation of data infrastructure needs to be understandable by agents as well as analysts. - High leverage - better models, pipelines, and tools multiply every data scientist and every stakeholder who depends on data. - Small team, broad scope - you'll have room to define standards, choose tools, and ship systems that become company-wide defaults.

Location: Spain Workplace: remote Team: Sales Operations Location: Fully remote, Spain Reports to: Head of Sales Ops The short version Our sales, account management and partnerships teams deal with our most important customers and partners. Sales Ops is the team that builds, improves and maintains the tools and processes they use to succeed. We are looking for a senior Salesforce developer who will fully own the platform and everything connected to it: the code, the architecture, the integrations, and the pipelines that move data in and out. This is the technical end of Sales Ops. You will decide how things are built, not just build what you are handed. What you'll do Own the Salesforce platform end to end. Over 100 users across 7 key teams, a data model that carries real weight, and a growing set of markets on top of it. You are accountable for how well the whole thing works and where it goes next. Build in Apex and Flow, and know which one the problem calls for. Triggers, classes, async processing, test coverage, and declarative automation where declarative is the right answer. You write code the next person can maintain, and you leave the org better structured than you found it. Own the integration layer. Connected tools, APIs and middleware. When data crosses a boundary, you know where it came from, what shape it should arrive in, and what breaks when it stops. Own ETL and reverse-ETL. Getting data into Salesforce and back out to the warehouse and the rest of the stack. You design these pipelines, you run them, and you fix them when they drift. Keep the connected stack healthy. Outreach, Modjo, Kubaru, Lusha, Clay, Hightouch and other tools. You don't need to arrive an expert in each, but you should become the person who understands how they fit together. Set the technical standard. Architecture decisions, review of what gets built declaratively versus in code, and honest calls about technical debt. You work alongside our Salesforce Administrator and Data Ops Analyst, and you are the technical reference point for both. Push the vision forward. We want all day-to-day sales work to happen in Salesforce: the data our teams need to see, the actions they need to take, and the AI and automation solutions that multiply their productivity. You are the person who makes the hardest parts of that possible. This is an individual contributor role. As the platform and the function grow, there may be opportunities for it to develop toward technical leadership, depending on business needs and how the team evolves. How we build Three principles guide everything we ship: Top user experience. Minimise admin work for our users, maximise their productivity. Their time is the point. Build it right. Efficient, scalable, adaptable. We dislike technical debt and we don't pretend it isn't there. Security and privacy. Customer and prospect data safety is not a checkbox at the end of a project, it's a foundational requirement in everything we do. What you bring 5+ years Salesforce Sales Cloud development experience supporting commercial teams. Strong Apex development: triggers, classes, asynchronous processing, governor limits, testing. You can read an unfamiliar org and work out what is safe to change. Strong Flow development, and the judgement to know when a Flow is the right tool and when it isn't. Deep understanding of permissions, sharing models and data architecture in Salesforce. Hands-on experience building and owning ETL and reverse-ETL processes, not just consuming them. Experience using AI as part of how you work, preferably with Agentforce or Claude, including at least one project where you delivered clear and demonstrable value to a stakeholder team. You can walk us through what you built, what changed, and how you know it mattered. You can turn a vague request into a spec, and you push back when the request is the wrong fix for the real problem. An obsession with making your Salesforce users happy. This is not a back-office role. You will hear directly when something is annoying, and you should want to hear it. Fluent English. Our team and company include people from many European countries, English is our common language. You love independence and hold yourself accountable. This is a full remote position and micromanagement is not something we do. Bonus points Experience with Salesforce Service Cloud. Salesforce Platform Developer I or II certification. Experience with Outreach, Clay or Hightouch. Experience with Databricks, BigQuery or Snowflake. Experience working in Fintech, banking or other highly regulated environments.

Smartsheet is seeking a Director, Finance Systems & ERP to lead the engineering organization responsible for the company's financial technology ecosystem and define the long-term technical strategy for platform evolution. The role involves owning the architecture, engineering maturity, technical health, and delivery of systems supporting core financial operations, procurement, planning, payments, billing, revenue processes, and emerging monetization models. This strategic and highly visible leadership position includes leading major transformation initiatives such as ERP modernization, billing transformation, and evolving usage-based and consumption-based monetization. The Director will represent Corporate Systems in executive steering committees and major transformation programs, partnering with Finance, Accounting, Procurement, Product Engineering, Sales/GTM, Data, and other technology leaders. Responsibilities: — Own the technical strategy and long-term architecture for Smartsheet’s financial systems ecosystem across ERP, procurement, financial planning, payments, billing, tax, revenue processes, integrations, data, automation, and AI — Lead, coach, and develop the Financial Systems Engineering organization responsible for platforms including NetSuite, Coupa, Planful, Stripe, ZoneBilling, Metronome, Avalara, and associated technologies — Serve as the senior technology leader for NetSuite and ERP, ensuring scalability, maintainability, security, auditability, and alignment with long-term SaaS business needs — Provide technology leadership for major Finance transformation programs, including ERP reimplementation and modernization — Partner with Product Managers to translate product strategy and business priorities into technical roadmaps and engineering plans — Shape technology architecture to support evolving SaaS monetization models including subscription, multi-year, usage-based, consumption-based, and AI-related pricing and billing — Establish architectural boundaries and systems of record across CRM, product, billing, ERP, payments, tax, planning, and downstream data platforms — Define strategy for Finance systems data including authoritative sources, data models, contracts, quality, lineage, reconciliation, and enterprise data platform consumption — Collaborate with Data Engineering and Analytics to integrate Financial Systems with enterprise data lake ensuring timely, trustworthy, and usable Finance data — Drive data quality and observability across Quote-to-Cash and Finance workflows — Establish AI strategy for Financial Systems Engineering to improve productivity, operations, controls, testing, support, reconciliation, and employee experiences — Evaluate and introduce AI-assisted capabilities ensuring financial integrity, security, auditability, human oversight, and controls — Develop strategy for automated testing and quality engineering across Finance technology stack — Establish modern engineering practices including source control, peer review, CI/CD, environment management, automated testing, observability, documentation, release engineering, and operational readiness — Determine boundaries between native SaaS configuration, platform extensibility, APIs, integrations, automation, and custom software — Partner with Integration Engineering to ensure scalable, observable, resilient Finance and Quote-to-Cash integrations — Own technical health and lifecycle of Financial Systems portfolio addressing architectural debt, platform limitations, fragile integrations, unnecessary customization, manual processes, and operational problems — Establish architecture reviews, technical standards, engineering metrics, platform health reviews to improve Financial Systems Engineering maturity — Represent Financial Systems Engineering on executive steering committees and transformation governance forums — Provide technical leadership across implementation partners and strategic vendors ensuring adherence to Smartsheet’s architecture and engineering standards — Partner with Finance leadership and stakeholders to understand business strategy while maintaining technology ownership — Balance delivery of transformation programs with operational reliability, roadmap commitments, technical debt reduction, platform modernization, security, controls, and long-term investments — Build partnerships across Finance, Product Engineering, Sales/GTM, Data, Security, AI & Automation, and Corporate Systems — Recruit, develop, and retain engineering talent with expertise in Finance platforms, software engineering, systems thinking, and financial technology innovation Requirements: — 10+ years of progressively responsible experience in financial systems, enterprise application engineering, ERP, software engineering, systems architecture, or related technical disciplines — 5+ years of experience leading technical teams including managing managers, senior engineers, architects, or technical leaders — Deep experience with NetSuite or comparable enterprise ERP platforms with technical depth to lead architecture and establish long-term platform strategy — Experience leading major ERP implementation, reimplementation, or transformation programs from architecture through ongoing evolution — Strong understanding of financial business processes including record-to-report, procure-to-pay, order-to-cash, billing, payments, financial planning, accounting, and revenue workflows — Experience with financial platforms such as Coupa, Planful, Stripe, ZoneBilling, Metronome, Avalara, or comparable technologies — Experience with SaaS billing and monetization architectures including subscription and usage-based or consumption-based models — Strong systems thinking across ERP, CRM, product, billing, payments, integrations, data platforms, APIs, automation, and financial controls — Experience defining technical strategy and architecture beyond managing application delivery or support — Experience designing or evolving enterprise data architecture including systems of record, data models, interfaces, contracts, quality, reconciliation, governance, lineage, and consumption — Experience partnering with Data Engineering or Analytics organizations and integrating operational systems with platforms like Databricks or Snowflake — Experience establishing modern engineering practices including automated testing, CI/CD, source control, observability, release management, documentation, and operational readiness — Understanding of modern AI capabilities and practical applications of LLMs, agents, and intelligent automation with financial, security, and compliance risk management — Strong understanding of financial controls, auditability, security, data integrity, and compliance for business-critical financial platforms — Experience governing system integrators and technology vendors during large transformation programs — Experience partnering with Product Managers and senior business leaders to align business, product, and technical strategy — Ability to operate effectively from executive steering committees to detailed architecture reviews — Demonstrated ability to challenge legacy processes and lead technology and operating-model change — Excellent analytical, verbal, and written communication skills with executive presence — Bachelor’s degree in Computer Science, Information Systems, Engineering, Finance, Business, or related field or equivalent experience Conditions: — Full-time remote position based in the USA — Employer subsidized medical, vision, and dental coverage for full-time employees — 401k match (50% of contribution up to first 6% of eligible pay) — Monthly stipend for work and productivity support — Flexible Time Away Program plus Sick Time Off — Life insurance, short-term and long-term disability plans — 12 paid holidays per year — Up to 24 weeks of parental leave — Personal paid volunteer day — Professional growth and development opportunities including Udemy courses — Company funded perks including counseling membership, local retail discounts, and personal Smartsheet account — Teleworking options from any registered location in the U.S. — Competitive base salary range depending on location and experience — Eligible for market competitive incentive opportunity

Задачи: — Проводить проактивный поиск угроз и анализ цепочек атак (kill chain) в системах Stripe и внешних данных. — Применять и развивать многоуровневую таксономию FT3 для стандартизации разведданных об угрозах. — Сотрудничать с командами Fraud Intelligence, Fraud Ops, Strategy, Risk, Onboarding и Security для интеграции и автоматизации потоков разведданных. — Переводить результаты исследований в практические рекомендации по контролю угроз, включая политику, технические системы, рабочие процессы поддержки и механизмы обнаружения. — Использовать агентные автоматизированные тестовые фреймворки для моделирования поведения злоумышленников, проверки эффективности контролей и создания регрессионных сценариев. Требования: — Опыт не менее 5 лет в области разведки угроз, поиска угроз или технического реагирования на инциденты в кибербезопасности, борьбе с мошенничеством или доверительных доменах. — Опыт анализа больших и сложных наборов данных с использованием аналитических инструментов для выявления аномалий, анализа поведенческих трендов и решения сложных задач мошенничества. — Высшее образование (бакалавр или магистр) в области компьютерных наук, кибербезопасности или смежной технической области, либо эквивалентный практический опыт. — Экспертное владение Python и SQL, опыт автоматизации рабочих процессов, создания инструментов для расследований и запросов к большим данным. — Практический опыт анализа логов (приложений, API, сетевых событий), цифровой криминалистики и методологий киберрасследований. — Сильные коммуникативные навыки для перевода сложных технических исследований в понятные и применимые рекомендации для межфункциональных команд. Предпочтительные квалификации: — Глубокое понимание мотиваций, инфраструктуры и тактик злоумышленников, специфичных для финансового мошенничества (например, ATO, Card Testing, Credential Stuffing). — Знакомство с таксономиями FT3 или MITRE ATT&CK. — Владение платформами для обработки и анализа данных, такими как Databricks, Trino, PySpark, Pandas, Scikit-Learn. — Опыт работы с платформами разведки угроз (TIPs), тактическими потоками угроз, OSINT и разведданными о взломах. — Навыки создания или использования агентных LLM-инструментов, систем автоматизированного тестирования и фреймворков валидации контролей для моделирования поведения злоумышленников в масштабе. — Участие в отраслевых конференциях, вебинарах, группах обмена угрозами и наличие профессиональных сертификатов (например, GCTI, GCFA, OSCP).

Location: Remote, Canada; Remote, United States GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. An overview of this role Data Products integrates GitLab and third-party SDLC data, and builds the dashboards, APIs, and data products that turn it into trusted, interoperable intelligence for customers and internal teams. This is a 0 to 1 team and we are hiring for a foundational engineering role. That means you bring technical leadership through ambiguity, helping figure out what to build, making the foundational design decisions, and keeping delivery moving while the picture is still forming. You own the full lifecycle of what ships and stand behind it. What you'll bring Proven ability to influence as a Staff owning product or platform systems end to end across multiple engineering and product teams. High agency, i.e finds the owner, clarifies the path, makes the call, and keeps pushing until the work lands. Force multiplier and raise the people and the codebase around them Deep full-stack expertise, including strong proficiency in Go, Ruby and Node . Depth in at least one of analytics and metrics platforms, graph data systems, CDC and warehouse integration. Hands-on experience building production AI-powered tool orchestration. Experience operating multi-tenant systems across SaaS and self-managed deployment. Direct communicator who builds alignment across teams. Bias to write things down and make reasoning legible. What you'll own Architect how GitLab and third-party data is ingested, modeled, and synced into the knowledge graph as a near-real-time graph of the development ecosystem. Lead integration with external systems for business context (Jira, observability tools, Zendesk, ServiceNow), indexed into the graph. Architect the Data Marketplace so customers consume GitLab data through Snowflake, Databricks, and BigQuery with no engineering dependencies. Publish GitLab observability as OpenTelemetry and broker the data-sharing APIs. Define operational readiness for everything the team ships across GitLab.com, Dedicated, and Self-Managed. Translate an ambiguous 0 to 1 problem space into concrete, iterable roadmaps in partnership with Product, Design, and the graph backend team. Resolve cross-team dependencies across graph backend, AI Platform, and Infrastructure without escalating everything upward. Mentor senior and intermediate engineers through design reviews, pairing, and code review. Create organizational leverage through speed. You identify systemic bottlenecks, simplify processes, and design systems that dramatically improve execution velocity. Take part in on-call or operational support where your team’s ownership model requires it. About the team Data Products work across three surfaces: Dashboard and Reporting Framework Builds AI-native dashboard components so customers and internal teams can see engineering health and GitLab's impact across DORA, VSA, AI Impact, SDLC trends, security, and quality, and launch their own custom dashboards on the same framework. Internal Ingestion Ingests third-party data into the GitLab and power tools like Knowledge Graph, building connectors so that signals from systems like Jira, Zendesk, ServiceNow, and observability tools become one queryable, near-real-time graph of the developer ecosystem. External Ingestion External makes GitLab and Knowledge Graph data consumable outside the product, through marketplace listings, data-sharing APIs and SDKs, and co-branded partner products. We are a new team in a highly ambiguous, high-impact space, and we need engineers who can create clarity while building, make practical tradeoffs, unblock cross-team dependencies, and keep pushing until meaningful customer value lands. The base salary range for this role’s listed level is currently for residents of the United States only. This range is intended to reflect the role's base salary rate in locations throughout the US. Grade level and salary ranges are determined through interviews and a review of education, experience, knowledge, skills, abilities of the applicant, equity with other team members, alignment with market data, and geographic location. The base salary range does not include any bonuses, equity, or benefits. See more information on our benefits and equity . Sales roles are also eligible for incentive pay targeted at up to 100% of the offered base salary. United States Salary Range $152,800 — $259,200 USD How GitLab Supports Full-Time Employees Benefits to support your health, finances, and well-being Flexible Paid Time Off Team Member Resource Groups Equity Compensation & Employee Stock Purchase Plan Growth and Development Fund Parental Leave Please note that we welcome interest from candidates with varying levels of experience; many successful candidates do not meet every single requirement. Additionally, studies have shown that people from underrepresented groups are less likely to apply to a job unless they meet every single qualification. If you're excited about this role, please apply and allow our recruiters to assess your application. Country Hiring Guidelines: GitLab hires new team members in countries around the world. All of our roles are remote, however some roles may carry specific location-based eligibility requirements. Our Talent Acquisition team can help answer any questions about location after starting the recruiting process. Privacy Policy: Please review our Recruitment Privacy Policy. Your privacy is important to us. GitLab is proud to be an equal opportunity workplace and is an affirmative action employer. GitLab’s policies and practices relating to recruitment, employment, career development and advancement, promotion, and retirement are based solely on merit, regardless of race, color, religion, ancestry, sex (including pregnancy, lactation, sexual orientation, gender identity, or gender expression), national origin, age, citizenship, marital status, mental or physical disability, genetic information (including family medical history), discharge status from the military, protected veteran status (which includes disabled veterans, recently separated veterans, active duty wartime or campaign badge veterans, and Armed Forces service medal veterans), or any other basis protected by law. GitLab will not tolerate discrimination or harassment based on any of these characteristics. See also GitLab’s EEO Policy and EEO is the Law . If you have a disability or special need that requires accommodation , please let us know during the recruiting process .

Задачи: — Участие в проекте по data engineering, разработке и миграции конвейеров данных в облачной среде. Требования: — Опыт работы в Data Engineering. — Практические знания Python и Databricks. — Опыт построения, поддержки и миграции data pipelines. — Опыт работы с потоковыми решениями, такими как Azure Event Hub и Apache Kafka. — Знание технологий обработки данных в реальном времени, включая Apache Druid и Apache Storm. — Хорошее понимание облачных платформ данных, предпочтительно Microsoft Azure. Дополнительные преимущества: — Знание Java для работы с существующими системами и legacy-кодом. — Опыт в веб-аналитике. — Опыт внедрения CI/CD. — Опыт в DevOps / DataOps. — Участие в инициативах по миграции данных. — Знакомство с Agile / Scrum. Условия: — Старт: ASAP / сентябрь 2026. — Контракт до 31 декабря 2026. — Полная занятость (100%). — Полностью удалённая работа (EU Remote). — Требуемый уровень английского: C1 (немецкий — плюс). — Методология работы: Scrum.