Вакансии

Задачи: — Проектирование, разработка и сопровождение ETL/ELT-процессов с использованием Python и Apache Airflow. — Разработка распределённых процессов пакетной обработки данных с использованием Apache Spark (PySpark), Trino и Apache Iceberg. — Проектирование, построение и оптимизация аналитических витрин данных в ClickHouse и PostgreSQL с использованием dbt. — Организация загрузки данных из реляционных баз данных, брокеров сообщений и внешних REST API. — Анализ и оптимизация производительности SQL-запросов, партиционирования таблиц и хранения данных. — Внедрение автоматизированных проверок качества данных, механизмов оповещения и процессов CI/CD для развертывания решений. Требования: — Практический опыт эксплуатации Apache Airflow, Spark (PySpark), ClickHouse и PostgreSQL в промышленной среде. — Знание Trino и Apache Iceberg будет преимуществом. — Уверенное владение Python и продвинутый уровень SQL, включая индексацию и анализ планов выполнения запросов. — Опыт работы в области Data Engineering от 3 лет, включая разработку сквозных конвейеров обработки данных и аналитических витрин. — Уверенный опыт работы с dbt для трансформации, тестирования и моделирования данных. Условия: — Официальное трудоустройство. — Ежегодный трудовой отпуск + 2 оклада. — Профессиональный рост и развитие. — Участие в архитектурных решениях. — График работы: 5/2, с 08:00 до 17:30. — Место работы: г. Астана, EXPO C2.3.

Задачи: — построение ETL-процессов: разработка и настройка конвейеров по сбору и трансформации данных из различных источников; — работа с современным стеком трансформации: освоение и применение DBT для превращения «сырых» данных в чистые аналитические витрины; — оркестрация данных: настройка и поддержка рабочих процессов (pipelines) в Dagster для своевременного и безошибочного обновления данных в отчетах; — управление хранилищами: работа с Postgres и высокопроизводительной колончатой базой данных Clickhouse для обеспечения скорости работы отчетов; — визуализация смыслов: разработка интерактивных BI-отчетов в Apache Superset для поддержки бизнес-решений; — оптимизация выборок: анализ и ускорение тяжелых запросов для повышения производительности системы отчетности. Требования: — уверенное владение SQL (сложные выборки, агрегатные функции, оптимизация запросов); — понимание устройства реляционных баз данных, в частности PostgreSQL, и принципов построения аналитических хранилищ; — базовые знания Python, умение писать скрипты для обработки данных и автоматизации простых задач; — аналитический склад ума, способность работать с большими массивами данных, выявлять закономерности и структурировать информацию. Желательный опыт: — опыт создания дашбордов в BI-инструментах (Apache Superset, Tableau, Power BI или аналогичных); — понимание концепций ETL/ELT; — понимание архитектуры данных, разницы между OLTP и OLAP системами (например, использование Clickhouse для аналитики); — интерес к современным инструментам DBT и оркестраторам данных (Airflow, Dagster). Условия: — срочный трудовой договор на 3 месяца; — график 5/2, не более 30 часов в неделю; — возможна удалённая, офисная или гибридная работа; — стажировка доступна студентам любых ВУЗов и форм обучения, включая заочную и магистратуру.

Задачи: — Проектирование и оптимизация ClickHouse: MergeTree, партиционирование, TTL, шардирование, репликация, бэкапы в S3. — ETL/ELT и оркестрация с использованием Airflow, dbt, обеспечение качества данных, тестирование, мониторинг свежести данных, data contracts. — Управление командой: найм, онбординг, развитие, performance review, процессы разработки, roadmap, OKR, бюджет. — Взаимодействие с бизнесом и Data Governance: сбор требований, приоритизация, коммуникация с C-level, каталог данных, lineage, соблюдение GDPR/152-ФЗ, разграничение доступа. Условия: — Удалённая работа из любой точки мира. — Конкурентная зарплата и performance премия 2 раза в год. — Гибкий график с фокусом на результат. — Оплата обучения, курсов и конференций. — Возможность влиять на продукт и команду.

Задачи: — Писать понятные и структурированные тест-кейсы — Создавать, поддерживать и приоритизировать backlog багов — Проводить функциональное и исследовательское тестирование — Выполнять регрессионное тестирование в рамках регулярных релизов — Следить за тем, чтобы тестирование оставалось неотъемлемой частью процесса разработки и поставки продукта — Анализировать требования и выявлять потенциальные проблемы на ранних этапах — Самостоятельно локализовывать, воспроизводить и описывать найденные проблемы — Тестировать REST API Требования: — От 3 лет опыта тестирования веб-приложений — Уверенное знание техник тест-дизайна — Опыт тестирования REST API — Базовое понимание HTTP — Умение самостоятельно анализировать и воспроизводить проблемы — Английский язык - B1 или выше, достаточный для чтения технической документации и рабочей коммуникации Будет преимуществом: — Опыт работы с SQL — Опыт работы с OpenSearch и Prometheus — Опыт работы с BrowserStack — Опыт работы с Apache Airflow — Понимание DAG, зависимостей между задачами, retries и обработки ошибок — Хорошие troubleshooting skills — Внимательность к деталям и умение работать с несколькими задачами одновременно Условия: — Оплачиваемые отпуска, больничные, праздники по ТК РФ — Корпоративный лэптоп

Location: Worldwide Workplace: remote We are looking for a Data Engineer to join our team.Requirements: 3+ years of experience in data engineering; Strong SQL: complex analytical queries and query optimization; Strong Python: solid fundamentals and hands-on experience with DE libraries (e.g., pandas, SQLAlchemy, PySpark); Software engineering background: you write production-grade Python, not just scripts (OOP, app architecture, testing, Git, CI/CD); Hands-on experience with Airflow (building and maintaining DAGs); Experience with dbt (models, tests, macros); ClickHouse: table engines, Materialized Views, performance tuning; Kafka: producers/consumers, topics and partitioning, delivery guarantees; Experience with data quality tools (e.g., dbt tests, Great Expectations, Soda); Solution-oriented mindset and ownership of results.Responsibilities: Support and develop our in-house data enrichment solution built on event sourcing; Build production-ready data marts using Airflow, dbt, and ClickHouse Materialized Views; Implement data quality checks for Airflow DAGs and ClickHouse MVs; Automate repetitive tasks and establish Data Engineering best practices and standards; Write and maintain technical documentation.We offer:High salary (plus performance bonuses and salary revision);Remote work;Work schedule: Mon-Fri (8 hours per day) with flexible starting hours;24 days holiday leave;Corporate English lessons;Exciting work challenges that allow you to grow to your full potential;A strong team of like-minded professionals who will be by your side to accomplish ambitious projects, stimulate your professional development and bring experience.

Location: Limassol, Cyprus We are looking for a Data Engineer to join our team.Requirements: 3+ years of experience in data engineering; Strong SQL: complex analytical queries and query optimization; Strong Python: solid fundamentals and hands-on experience with DE libraries (e.g., pandas, SQLAlchemy, PySpark); Software engineering background: you write production-grade Python, not just scripts (OOP, app architecture, testing, Git, CI/CD); Hands-on experience with Airflow (building and maintaining DAGs); Experience with dbt (models, tests, macros); ClickHouse: table engines, Materialized Views, performance tuning; Kafka: producers/consumers, topics and partitioning, delivery guarantees; Experience with data quality tools (e.g., dbt tests, Great Expectations, Soda); Solution-oriented mindset and ownership of results.Responsibilities: Support and develop our in-house data enrichment solution built on event sourcing; Build production-ready data marts using Airflow, dbt, and ClickHouse Materialized Views; Implement data quality checks for Airflow DAGs and ClickHouse MVs; Automate repetitive tasks and establish Data Engineering best practices and standards; Write and maintain technical documentation.We offer:High salary (plus performance bonuses and salary revision);Work schedule: Mon-Fri (9h with 1h lunch break), flexible start 8:00-10:00;24-days holiday leave;First line seaview from your office;Corporate English and Greek lessons;GYM and SPA in the office;Corporate meals;Eventful corporate life;Exciting work challenges that allow you to grow to your full potential;Strong team of like minded professionals who will be by your side to accomplish ambitious projects, and to stimulate your professional development and bring experience.

Задачи: — Разрабатывать и совершенствовать платформу данных электронной коммерции нового поколения — Проектировать и разрабатывать ETL пайплайны на Airflow для Spark (Batch, Streaming), Iceberg, Trino — Оптимизировать действующие пайплайны и джобы на Spark, мониторить нагрузку на кластер и оптимальность ресурсов, при необходимости оптимизировать — Взаимодействовать с аналитиками и ML специалистами для создания и развертывания инструментов и наборов данных, поддерживать связи с data ops для развития дата-платформы — Анализировать и внедрять инструменты инжиниринга данных (Lineage, DQ) — Проектировать хранилища данных на основе Kubernetes, настраивать производительность, мониторинг, планировать емкости кластера и инфраструктуры — Решать задачи, связанные с внедрением облачной инфраструктуры, разрабатывать новую архитектуру хранилища — Проводить code review и участвовать в архитектурных решениях по дата платформе Требования: — Понимание ресурсной модели Kubernetes, просмотр конфигураций, troubleshooting — Опыт работы с Hadoop (HDFS, Hive Metastore) — Опыт работы со Spark (spark SQL, streaming, понимание нюансов работы с pyspark) — Владение процедурами, snapshots, maintenance Apache Iceberg — Глубокое понимание Airflow (версии 2, 3), включая идемпотентность, assets, backfills — Уверенное знание Git, CI/CD — Знание Python, Scala/Java, ООП, проектирование библиотек, интеграционные и юнит тесты — Хорошее понимание СУБД, SQL Будет плюсом: — Опыт работы с Docker для поднятия локального окружения проекта — Опыт работы с Kafka, понимание архитектуры и слабых мест — Опыт с облачными технологиями, преимущественно Yandex Cloud — Опыт с Clickhouse — AI-native подход к разработке: использование Claude Code / Codex и подобных инструментов, опыт построения harness-систем — агентов с инструментами, автоматизации через LLM, RAG

Location: Singapore About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. Mechanical Design Engineer – Data Centres Nebius We’re looking for a Mechanical Design Engineer to help shape the mechanical infrastructure supporting our data centre developments. You’ll contribute throughout the project lifecycle, from concept design and technical assessments through detailed design, construction and commissioning. Working alongside electrical engineers, IT infrastructure teams, external consultants and equipment suppliers, you’ll develop practical, scalable cooling solutions for high-density computing environments. This is an opportunity to influence engineering decisions, help develop design standards and see your work carried through into operating facilities. What you’ll do Develop and review mechanical designs for new data centres, expansions and upgrades. Produce and assess cooling calculations, equipment specifications, schematics, layouts and design documentation. Evaluate cooling systems, including chillers, pumps, heat exchangers, air-handling equipment and associated pipework. Support the integration of liquid cooling, coordinating the interfaces between facility systems, coolant distribution units and IT equipment. Assess capacity, redundancy, maintainability and system performance under normal operation, maintenance and failure conditions. Coordinate mechanical designs with electrical, structural, architectural and controls teams, including airflow, containment and plant-space requirements. Review consultant designs, supplier proposals and contractor submissions, resolving technical queries during procurement and construction. Support site assessments, installation reviews and commissioning to verify that systems meet the design requirements. Identify opportunities to improve energy and water efficiency, reduce lifecycle costs and standardise designs across projects. What you’ll bring A qualification in Mechanical Engineering, Building Services Engineering or equivalent practical experience. Experience designing mechanical systems for data centres or other mission-critical facilities. Strong knowledge of HVAC, cooling systems, heat transfer, fluid distribution and equipment selection. An understanding of resilient design and the operational requirements of facilities running continuously. Experience preparing or reviewing engineering calculations, technical specifications and construction documentation. Familiarity with mechanical controls and Building Management System interfaces. The ability to work effectively with consultants, contractors, suppliers and colleagues across engineering disciplines. Clear communication skills in English and willingness to travel to project sites when required. Useful additional experience Direct-to-chip liquid cooling or other cooling technologies for high-density AI and HPC environments. Thermal modelling, airflow analysis or computational fluid dynamics. BIM coordination and tools such as Revit or AutoCAD. Commissioning, integrated systems testing or operational troubleshooting. Professional engineering registration or relevant data centre qualifications. Benefits & Perks: Competitive compensation Career growth and learning opportunities Flexibility and ownership Collaborative and innovative culture Opportunity to work on impactful AI projects International environment and talented teams What's it like to work at Nebius: Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.

Location: Amsterdam, Netherlands About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. Mechanical Design Engineer – Data Centres Nebius We’re looking for a Mechanical Design Engineer to help shape the mechanical infrastructure supporting our data centre developments. You’ll contribute throughout the project lifecycle, from concept design and technical assessments through detailed design, construction and commissioning. Working alongside electrical engineers, IT infrastructure teams, external consultants and equipment suppliers, you’ll develop practical, scalable cooling solutions for high-density computing environments. This is an opportunity to influence engineering decisions, help develop design standards and see your work carried through into operating facilities. What you’ll do Develop and review mechanical designs for new data centres, expansions and upgrades. Produce and assess cooling calculations, equipment specifications, schematics, layouts and design documentation. Evaluate cooling systems, including chillers, pumps, heat exchangers, air-handling equipment and associated pipework. Support the integration of liquid cooling, coordinating the interfaces between facility systems, coolant distribution units and IT equipment. Assess capacity, redundancy, maintainability and system performance under normal operation, maintenance and failure conditions. Coordinate mechanical designs with electrical, structural, architectural and controls teams, including airflow, containment and plant-space requirements. Review consultant designs, supplier proposals and contractor submissions, resolving technical queries during procurement and construction. Support site assessments, installation reviews and commissioning to verify that systems meet the design requirements. Identify opportunities to improve energy and water efficiency, reduce lifecycle costs and standardise designs across projects. What you’ll bring A qualification in Mechanical Engineering, Building Services Engineering or equivalent practical experience. Experience designing mechanical systems for data centres or other mission-critical facilities. Strong knowledge of HVAC, cooling systems, heat transfer, fluid distribution and equipment selection. An understanding of resilient design and the operational requirements of facilities running continuously. Experience preparing or reviewing engineering calculations, technical specifications and construction documentation. Familiarity with mechanical controls and Building Management System interfaces. The ability to work effectively with consultants, contractors, suppliers and colleagues across engineering disciplines. Clear communication skills in English and willingness to travel to project sites when required. Useful additional experience Direct-to-chip liquid cooling or other cooling technologies for high-density AI and HPC environments. Thermal modelling, airflow analysis or computational fluid dynamics. BIM coordination and tools such as Revit or AutoCAD. Commissioning, integrated systems testing or operational troubleshooting. Professional engineering registration or relevant data centre qualifications. Benefits & Perks: Competitive compensation Career growth and learning opportunities Flexibility and ownership Collaborative and innovative culture Opportunity to work on impactful AI projects International environment and talented teams What's it like to work at Nebius: Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.

Задачи: — Разработка, сопровождение и ревью ETL-процессов поставки данных. — Создание конвейеров для извлечения, трансформации и загрузки данных из различных источников, настройка расписания и мониторинга. — Регулярная проверка и улучшение существующего кода, оперативное исправление ошибок, тщательное документирование всех преобразований и потоков данных. — Проектирование структуры хранения данных в разных слоях хранилища, разработка моделей данных, настройка партиционирования, индексации и сжатия для повышения производительности. — Согласование структур с командами аналитики и разработки, адаптация схем при изменении бизнес-процессов. — Выявление и оптимизация неэффективных участков в процессах поставки данных, анализ времени выполнения ETL-задач, профилирование данных для обнаружения аномалий и избыточности, пересмотр алгоритмов трансформации. — Погружение в данные прикладных бизнес-областей, изучение бизнес-процессов и ключевых метрик компании, разбор логики расчёта показателей и источников их формирования. Требования: — Опыт проектирования DWH (слои, модели хранения данных, ETL-процессы). — Разработка ETL-процессов на Apache Airflow или аналогах. — Настройка поставок данных по API. — Экспертное знание SQL. — Программирование на одном из языков высокого уровня (Python, Go, Java и др.). — Понимание устройства и архитектуры реляционных баз данных. — Знание основных алгоритмов и структур данных, особенно применяемых в работе с большими данными. Будет плюсом: — Опыт работы с MPP-СУБД (Greenplum, ClickHouse, Vertica, Teradata и др.). — Понимание принципов работы технологий распределённой обработки данных (Hadoop, MapReduce, MPP). Условия: — Работа с инфраструктурой и данными Яндекса, масштабные задачи. — Влияние на эффективность ключевых бизнес-процессов. — Возможность обмена опытом с ведущими специалистами отрасли и профессионального роста. — Доступ к передовым технологиям и инструментам. — Карьерные перспективы внутри одной из ведущих IT-компаний России.

Задачи: — Владение программой управления инцидентами конфиденциальности от начала до конца, включая рабочие процессы уведомлений, пути эскалации, документацию процессов, обучение ответственных и возможности автоматизации. — Руководство реагированием на инциденты конфиденциальности в роли DRI и Incident Commander, координация между отделами Privacy, Privacy Legal, CSIRT, Product, Engineering и Communications для анализа, устранения и последующих действий. — Поддержание готовности к вызову для поддержки триажа инцидентов конфиденциальности, классификации серьезности и срочных эскалаций, обеспечение правильной оценки и маршрутизации инцидентов. — Проведение ретроспектив по инцидентам конфиденциальности, отслеживание элементов устранения и пробелов в контроле, предоставление метрик и отчетности по тенденциям, статусу устранения и состоянию процессов. — Построение и поддержание прочных межфункциональных и межгеографических отношений с заинтересованными сторонами для улучшения готовности, качества реагирования и ответственности бизнеса. — Поддержка более широких инициатив Privacy в периоды низкой загрузки, включая межфункциональные усилия, разработку инструментов и проекты автоматизации. Требования: — Опыт работы 3+ года в области конфиденциальности, безопасности, реагирования на инциденты, технологических рисков или смежных операционных рисков, включая опыт руководства или поддержки рабочих процессов инцидентов, вопросов или рисков с необходимостью структурированного анализа, документации и межфункциональной координации. — Сильные навыки управления инцидентами с опытом коммуникации рисков конфиденциальности и результатов инцидентов как технической, так и нетехнической аудитории, включая подготовку письменных анализов инцидентов, документации ретроспектив и резюме для руководства. — Подтвержденный опыт проведения технических расследований в облачных архитектурах с практическими навыками в SQL, Python и инструментах анализа данных (Postgres, MongoDB, Airflow, Looker, Snowflake). — Опыт создания автоматизации для сокращения ручных операций и повышения эффективности реагирования на инциденты. — Знание нормативных актов и рамок конфиденциальности (GDPR, CCPA, PIPEDA, ePrivacy, DPIAs/PIAs, ROPA, права субъектов данных), контролей конфиденциальности и управления вопросами конфиденциальности. — Ответственное использование и создание генеративного ИИ с сохранением человеческого контроля для обеспечения готовых к бизнесу результатов и повышения эффективности рабочих процессов, снижения затрат и улучшения качества. Условия: — Полная занятость. — Удалённая работа с обязательными квартальными очными сессиями (surges). — Годовой базовый оклад от $135,320 до $159,200 USD, возможны акции, бонусы и социальные льготы (медицинская страховка, стоматология, зрение, 401(k)). — Кандидаты могут подать максимум 3 заявки за 6 месяцев. — Компания является работодателем с равными возможностями.

Location: EMEA About Prefect Prefect builds automation for an unpredictable world. The last decade of automation was about protecting workflows from unpredictability; in the agentic era, unpredictability is the point. Our mission is to give people confidence in automated work, whether that work is a mission-critical data pipeline or a fleet of AI agents. In August 2026, Prefect and Dagster, competitors for eight years, joined forces to build the next generation of automation infrastructure. Today, our ecosystem includes Dagster, the data platform; Prefect, the agent platform; and FastMCP, the leading open-source developer framework for the MCP ecosystem. Together, our open-source and commercial products are trusted by Fortune 500 companies, data innovators, and high-growth technology companies around the world. We think of our culture as the operating system of the company. We’ve carefully created a supportive, high-performance environment that empowers our team to do the best work of their careers, have meaningful impact, and continue growing personally and professionally. We’re a remote-first team that values high standards, ownership, and thoughtful collaboration. ABOUT PREFECT Prefect builds automation for an unpredictable world. The last decade of automation was about protecting workflows from unpredictability; in the agentic era, unpredictability is the point. Our mission is to give people confidence in automated work, whether that work is a mission-critical data pipeline or a fleet of AI agents. In August 2026, Prefect and Dagster, competitors for eight years, joined forces to build the next generation of automation infrastructure. Today, our ecosystem includes Dagster, the data platform; Prefect, the agent platform; and FastMCP, the leading open-source developer framework for the MCP ecosystem. Together, our open-source and commercial products are trusted by Fortune 500 companies, data innovators, and high-growth technology companies around the world. We think of our culture as the operating system of the company. We’ve carefully created a supportive, high-performance environment that empowers our team to do the best work of their careers, have meaningful impact, and continue growing personally and professionally. We’re a remote-first team that values high standards, ownership, and thoughtful collaboration. ROLE SUMMARY Developer Success is the technical support function for Prefect's customers across the Prefect and Dagster product lines. Its mission is to resolve customer technical issues with the least possible customer effort, and to prevent those issues from recurring. We are hiring a Developer Success Engineer to work the combined Prefect and Dagster support queue. You will diagnose and resolve technical issues in customer environments, own each issue through resolution, and contribute to the documentation, tooling, and product feedback that reduce future volume. You will be trained on both Prefect’s and Dagster’s products. The team is investing in agent-based automation for routine support work, which is moving the engineering focus toward complex diagnosis and escalation. This role is well suited to an engineer who wants to build deep expertise in orchestration and data platform environments and apply it directly with customers. WHAT YOU'LL DO - Clear the failure state, and prevent the next one. Diagnose problems across Prefect and Dagster installations, integrations, deployments, and the cloud and container environments they run in. Find the underlying "why" so your first response resolves the question and pre-empts the follow-ups. Turn what you learn into docs, debugging resources, and tooling that deflect repeat submissions. - Own what's ours; say no clearly to what isn't. Take full accountability for root causes inside our products' domain of control. For problems outside our Scope of Support, issue a principled no that still gives the customer a way forward. Helplessness erodes trust as fast as a wrong answer. - Support your findings, and ask customers to support theirs. Back every diagnosis with evidence and logic. Assume the customer is the expert on their own stack, ask for what you need to troubleshoot both sides of an issue, and explain why you need it. Leave room for the possibility you've missed something. - Give the best possible update every time, and say so when you're still building it. A half-baked answer sent fast is worse than a complete one sent when it's ready; but radio silence is worse than both. When an issue needs to be escalated, you stay the customer's single point of contact, keep them updated on a regular cadence, and close the loop. - Feed the product. File reproducible product issues and surface recurring failure patterns to Engineering and Product. You'll work the queue independently on day-to-day issues and own moderate-complexity problems end to end, including investigations across a customer's cloud environment. You'll ask when the Scope of Support or an escalation path is unclear, and you'll build the judgment to recognize when an issue belongs with Customer Engineering or a CSM instead. We measure the role on Customer Effort Score and resolution time, held in tension: a fast answer that costs the customer effort isn't a good one. Timezone & on‑call: Available to work 09:00 – 18:00 CET (UTC ± 2) and participate in the 24/7 on‑call rotations. YOUR QUALIFICATIONS Must have: - Python fluency at the level of reading and debugging someone else's code, not only writing your own. - Hands-on experience running workloads in at least one major cloud and in containers or Kubernetes, enough to troubleshoot a deployment you didn't build. - Experience with a workflow orchestrator (Prefect, Dagster, Airflow, or comparable) and a strong interest in the data engineering space it lives in. - A track record of technical, customer-facing work: support, solutions engineering, developer relations, or similar. - Clear enough written communication to explain a root cause to a skeptical senior engineer and earn their trust. Nice to have: - Direct experience with Prefect or Dagster specifically. - A history of open-source contribution, in any project. - SQL and data warehouse familiarity. - Experience building support tooling or automation. WHAT TO EXPECT This is a support role. There's a queue, a Scope of Support, and an on-call rotation, and the first job is always the failure state in front of you. If a defined scope and a real customer on the other end of every problem sounds like the point, this is the role. While engineers on this team do contribute code and take on consultative work, the queue comes first. Those opportunities will progressively open up as the agent tooling absorbs the formulaic work. WHAT YOU'LL GET IN RETURN Base Salary Ranges: We offer competitive salary in local currency. Actual base salary within each range depends on the candidate's location, experience, and qualifications. Please keep in mind that equity and benefits are not included in the range provided above. Your recruiter can share more about the salary range for your preferred location during the hiring process. Perks and Benefits: - Remote-first team with flexible-first culture - Equity Stock Options - 401(k) with 5% company match (vests immediately!) - Unlimited PTO - Medical, Dental and Vision insurance - Generous Parental Leave - Life Insurance and Disability benefits - $800/month remote work stipend And that's just the start — for more info check out our benefits and perks on our careers page. BELONGINGNESS AT PREFECT: Belongingness at Prefect is our commitment to ensuring mutual power, access, and opportunity among all groups and individuals who make up our community. We operationalize belongingness through actions large and small on a daily basis, but always with the goal that all groups and individuals can contribute as their most authentic self to the evolution of our product, our team, and our community. Belongingness is also our commitment to bridge with individuals or groups not yet established in our community, acknowledge differences in a way that affirms distinct identities, and allows for a new, more expansive group identity to form. EQUAL OPPORTUNITY AT PREFECT: Prefect is an equal opportunity employer and encourages applications from people of all backgrounds. All applicants will be considered for employment without attention to race, religion, color, sex (including pregnancy, sexual orientation and gender identity/expression), national origin, disability or any other status protected under applicable federal, state, or local laws. Delaney is a real live person (👋🏻) and is looking forward to learning more about you through your application.

Location: United States & Canada Workplace: Remote About WorkOS 🚀 WorkOS builds modern developer tools and APIs that make it easy for companies to become Enterprise Ready. Our platform powers authentication, identity, authorization, and other critical infrastructure that developers need to securely scale their products to large organizations. We recently raised a $100M Series C, valuing the company at $2B, led by Meritech and Sapphire with participation from Greenoaks, Craft, Abstract, and Audacious. WorkOS powers enterprise features for many of the fastest-growing AI companies, including OpenAI, Cursor, and Perplexity, Sierra, and Plaid. As AI reshapes software, WorkOS is at the frontier of Human and Agent Authentication, Identity, and Access Control helping companies answer a new critical question: who are your agents, and what are they allowed to do? Our fast-growing customer base includes hundreds of modern software companies building the next generation of enterprise-ready products. ABOUT THE ROLE The Data team at WorkOS plays a central role on the company operations to ensure information and insights are accurate and available from any surface, whether that's a visualization tool or an agent's response, to accelerate company growth and scale. The team owns WorkOS's internal data platform end to end: ingestion, orchestration, the Snowflake warehouse, dbt transformations, governance and access controls. We also own the consumption layer: the reverse-ETL syncs that land data in Salesforce and Slack, the semantic views that agents query, the definitions that keep reporting consistent across the company, and the visualization tooling the company uses (ask us about Flashboards https://workos.com/blog/reporting-tool-with-no-editor). We run on an agent-first operating system: we are a lean team that moves fast, we document so agents can execute, and AI agents query the warehouse, run our runbooks, and open pull requests alongside us. We trust each other's expertise, we work out loud and in the open, and not opposed to rapid experimentation to get to the right solution for the business. We're hiring a Data Engineer to own and evolve the systems that move, transform, protect, and serve data across our internal warehouse. This is a high-ownership role on a lean team: you will be the DRI for the platform and its core data models, partner directly with Product Engineering, RevOps, Finance, GTM Engineering, and Security, and raise the bar on reliability, correctness, and operational rigor. The role spans the platform and what runs on it. You will own ingestion, orchestration, and access governance; the dbt models and metric definitions that depend on them; and how AI is applied across the data stack, so that trusted data is easy for both people and AI agents to discover, understand, and work with. You don't need to have done this exact job before. The best data engineers at WorkOS are the ones who notice in a Slack thread that a number doesn't match, trace it from the dashboard through the Gold model to the connector, fix the connector, and confirm the definition with its owner before the weekly review. When a business team asks for a field in Salesforce, they don't hand it off; they build the model, write the sync, and add the test. They would rather automate the runbook than run it a third time. They enjoy collaboration with different parts of the business and can find simple, scalable solutions to ambiguous problems. If that sounds like how you work, we want to talk. RESPONSIBILITIES - Own the reliability, freshness, and scaling of the ingestion and orchestration pipelines that land source data in Snowflake, including monitoring, alerting, runbooks, and backfill and reprocessing patterns - Design, build, and scale the core dbt models (Bronze, Silver, Gold) for billing and usage, CRM, product events, and GTM funnel reporting - Partner with Product, Finance, RevOps, and GTM to define metrics and codify them in the warehouse, and diagnose and resolve data quality and freshness issues at source, not just downstream - Own Snowflake RBAC, dynamic masking, and PII classification for humans, agents, and service accounts, so sensitive data is protected without blocking legitimate use, and review DDL and access requests from Engineering and GTM - Own the reverse-ETL layer and the runbooks that deliver warehouse data to Salesforce, Slack, and internal agents - Extend the semantic views, context, and evaluations that let agents answer business questions accurately, and expand what agents can operate directly, from runbooks and ingestion to pull requests - Build and advance the CI/CD review gates in the data-platform monorepo, including the automated review that agent-authored pull requests pass through - Own the infrastructure the data platform runs on: the compute, deployments, secrets and access patterns, and environments behind ingestion and orchestration, with attention to availability and failure modes, in partnership with our infrastructure engineers Example problems you might work on, possible paths rather than a fixed roadmap: - Standardizing how Postgres and SaaS sources are ingested, and consolidating end-to-end pipeline deployment and orchestration in Prefect - Managing Snowflake RBAC, resource management, and masking policies as code with Terraform - Using query history to improve analytics tables and semantic views, and to keep agent answers accurate and consistent as data grows and metrics shift - Automating masking coverage as new data sources arrive, so adding a new table no longer needs a human in the loop - Automating near-certain matches in the Identity Graph - Pseudonymizing product data in the ingestion path, alongside compliance and data-deletion policies - Extending transcript aggregation across sources, including PII detection before transcripts enter the warehouse - Building the reverse-ETL framework and runbooks that deliver data to other tooling and agents - Running self-hosted data services on Kubernetes and managing their AWS resources (IAM, storage, secrets) as code with Terraform QUALIFICATIONS - 5+ years (or equivalent) building and operating production data platforms, including the transformation layer - Deep experience with Snowflake, dbt, and an orchestrator such as Prefect, Airflow, or Dagster, and with ingesting data from production databases and SaaS sources, including backfill and reprocessing patterns - Experience running data systems in production: monitoring, alerting, debugging, incident response habits, and pragmatic SLO/SLA thinking - Experience with warehouse access governance: RBAC, masking policies, and PII handling - Strong data modeling judgment and an understanding of schema evolution - Strong SQL and Python; disciplined engineering practices (tests, docs, reviews, CI/CD) - Proven experience operating as the only engineer on a layer, balancing foundational architecture with urgent business needs - Working knowledge of how GTM, Finance, and Product teams operate in addition to working with Engineering, and experience translating ambiguous business questions into technical specs - Comfortable using LLMs and coding agents as part of your day-to-day development workflow, with the judgment to validate their output and scale it into shared processes, and embracing AI and automation to scale platform work and accelerate your teammates - A systems thinker who reasons carefully about freshness, correctness, and failure modes, especially for data that everything else depends on - Pragmatic: you start with the simplest solution that works, prove it, then scale it, and you balance fast answers with durable solutions - You look for where AI can remove a bottleneck for the people and agents who depend on the warehouse, and you build the durable tools and workflows they rely on every day Benefits and Perks (US Only) 💖 At WorkOS, we offer resources that emphasize personal and familial well-being. We offer healthcare coverage for you and your family, including medical, dental, and vision. We offer parental leave, paid-time off and fully remote working arrangements.   - 401k matching - Competitive Equity - Healthcare, dental and vision coverage - FSA, ST/LT Disability, Voluntary Life - Carrot fertility benefits - 20 days paid vacation + 10 holidays + unlimited sick leave - 12 weeks fully paid parental leave - Fitness: Monthly stipend for gyms, yoga classes, race registrations or whatever keeps you active - Wellness: Monthly stipend for a massage, meditations class, therapy, or activities that enhance your well-being - Commuter benefits for hybrid employees in SF/NYC - Unlimited token usage! Please inquire directly with our recruiting team for benefits available to those working outside the US.   Equal Opportunity Employer WorkOS is an equal opportunity employer, committed to diversity and inclusiveness. We will consider all qualified applicants without regard to race, color, nationality, gender, gender identity or expression, sexual orientation, religion, disability or age. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Location: Ukraine; Moldova; Latvia; Albania; North Macedonia; Slovakia; Malta; Croatia; Czech Republic; Slovenia; Romania; Spain; Bulgaria; Kazakhstan; Poland; Hungary; Montenegro; Estonia; European Union; Cyprus; Lithuania; Greece; Serbia; Bosnia; Georgia Workplace: Remote ABOUT US Ruby Labs is a leading tech company that creates and operates innovative consumer products. We offer a diverse range of opportunities across the health, education, and entertainment industries. Our innovative teams are driving the future of consumer-led products, and we're always looking for passionate individuals to join us. Learn more about our story at: https://rubylabs.com/about-us/ ABOUT THE ROLE Ruby Labs is hiring an experienced Senior Data Analyst to join our fast-paced, high-ownership environment. You will drive analytics across subscription products and web funnels, partnering with Product, Marketing (UAM), and Data teams to improve conversion, retention, and LTV- while ensuring trusted tracking, strong data models, and decision-ready reporting. This role is hands-on and cross-functional: you will own analysis from problem framing to recommendation, and you’ll mentor analysts while collaborating closely with Data Engineering/BI to keep data foundations reliable. RESPONSIBILITIES - Partner with Product, Marketing, and Data Teams to define KPIs, success metrics, and decision criteria. - Create new dashboards, maintain and improve existing reporting (e.g., Product Reports, Marketing Performance Reports), ensuring clarity and trust. - Deliver full-funnel analysis, identify bottlenecks, and propose improvements or A/B test ideas. - Lead user behavior analysis (journeys, drop-offs, activation/aha moments) using event data. - Monitor key metrics and anomalies; escalate issues and communicate updates to stakeholders with defined SLAs - Own and maintain event taxonomy and tracking structure (events, properties, naming conventions); validate implementation and business logic alignment. - Design and build robust, reusable SQL data models (clean layers, consistent definitions, performance-minded queries). - Mentor Junior/Middle Analysts in SQL, validation, funnel/cohort analysis, and experimentation quality; provide regular feedback and guidance. - Give and receive direct, actionable feedback with peers and the Leadership Team; maintain a high bar for quality in a demanding environment. REQUIREMENTS - Degree in an analytical field (e.g., Mathematics, Data Science, Economics) or equivalent practical experience. - 3+ years of experience as a Data Analyst, with proven ownership of end-to-end analysis and stakeholder delivery. - Strong analytical and problem-solving skills; ability to identify trends, patterns, and root causes in large datasets. - Excellent verbal and written communication; ability to translate analysis into clear business actions. - Ability to think strategically and make data-driven recommendations aligned with company goals. - Strong experience in Product Analytics: funnels, cohorts, retention, LTV, churn, segmentation. - Hands-on experience with event analytics tools: Mixpanel, GA4, Amplitude, or similar - Advanced SQL - Experience with popular BI tools such as Tableau, Looker, or similar - Experience in subscription business - Ability to adapt quickly, learn new tools and methods efficiently, and work effectively in a high-pressure, fast-changing environment NICE TO HAVES - Strong spoken and written English - Experience in Marketing Analytics - Experience with Python, R - Experience with GCP, BigQuery - Experience with Google Ads, Facebook Ads etc - Experience with orchestration frameworks such as Airflow, dbt - Experience with git and code review process LOCATION Ruby Labs operates within the CET (Central European Time) zone. Applicants from any country are welcome to apply for the position as long as they are located within approximately ± 4 hours of CET. This ensures optimal collaboration and communication during working hours. BENEFITS Discover the perks of being part of our vibrant team! We offer: - Remote Work Environment: Embrace the freedom to work from anywhere, anytime, promoting a healthy work-life balance. - Unlimited PTO: Enjoy unlimited paid time off to recharge and prioritize your well-being, without counting days. - Paid National Holidays: Celebrate and relax on national holidays with paid time off to unwind and recharge. - Company-provided MacBook: Experience seamless productivity with top-notch Apple MacBooks provided to all employees who need them. - Flexible Independent Contractor Agreement: Unlock the benefits of flexibility, autonomy, and entrepreneurial opportunities. Benefit from tax advantages, networking opportunities, reduced employment obligations, and the freedom to work from anywhere. Read more about it here: https://docs.google.com/document/d/1nkrN76JlZkbKj9WSOhlT1_mni_CZeDkHdwfIjPXVwvk/preview?tab=t.0#heading=h.ndsdl4wapxtt Be part of our fast-growing team and seize this excellent opportunity for personal and professional growth! INTERVIEW PROCESS After submitting your application, we conduct a thorough review which typically takes 3 to 5 days, but may occasionally take longer due to the volume of applications received. If we see a potential fit, we proceed with the following steps: - Recruiter Screening (40 minutes) - Technical Interview (90 minutes) - Final Interview (60 minutes) LIFE AT RUBY LABS At Ruby Labs, we move fast, aim high, and expect the same from our team. We’re not here to play small—we’re here to build, grow, and win. That means we look for people who are ambitious, driven, and ready to give their best every single day. This is a place for individuals who thrive under pressure, embrace challenges, and see opportunity in every obstacle. If you’re hungry to achieve, motivated by impact, and want to grow at the speed of your own ambition, Ruby Labs offers the platform to make it happen. Here, effort is matched with reward. We recognize those who go all in and deliver results, and we create space for people who want more—more responsibility, more growth, and more success. #LI-Remote

Location: Ukraine; Moldova; Latvia; Albania; North Macedonia; Slovakia; Malta; Croatia; Czech Republic; Slovenia; Romania; Spain; Bulgaria; Kazakhstan; Poland; Hungary; Montenegro; Estonia; European Union; Cyprus; Lithuania; Greece; Serbia; Bosnia; Georgia Workplace: Remote ABOUT US Ruby Labs is a leading tech company that creates and operates innovative consumer products. We offer a diverse range of opportunities across the health, education, and entertainment industries. Our innovative teams are driving the future of consumer-led products, and we're always looking for passionate individuals to join us. Learn more about our story at: https://rubylabs.com/about-us/ ABOUT THE ROLE Ruby Labs is hiring an experienced Lead Data Analyst to join our fast-paced, high-ownership environment. You will drive analytics across subscription products and web funnels, partnering with Product, Marketing (UAM), and Data teams to improve conversion, retention, and LTV- while ensuring trusted tracking, strong data models, and decision-ready reporting. This role is hands-on and cross-functional: you will own analysis from problem framing to recommendation, and you’ll mentor analysts while collaborating closely with Data Engineering/BI to keep data foundations reliable. RESPONSIBILITIES - Partner with Product, Marketing, and Data Teams to define KPIs, success metrics, and decision criteria. - Create new dashboards, maintain and improve existing reporting (e.g., Product Reports, Marketing Performance Reports), ensuring clarity and trust. - Deliver full-funnel analysis, identify bottlenecks, and propose improvements or A/B test ideas. - Lead user behavior analysis (journeys, drop-offs, activation/aha moments) using event data. - Monitor key metrics and anomalies; escalate issues and communicate updates to stakeholders with defined SLAs - Own and maintain event taxonomy and tracking structure (events, properties, naming conventions); validate implementation and business logic alignment. - Design and build robust, reusable SQL data models (clean layers, consistent definitions, performance-minded queries). - Mentor Junior/Middle Data Analysts in SQL, validation, funnel/cohort analysis, and experimentation quality; provide regular feedback and guidance. - Give and receive direct, actionable feedback with peers and the Leadership Team; maintain a high bar for quality in a demanding environment. REQUIREMENTS - Degree in an analytical field (e.g., Mathematics, Data Science, Economics) or equivalent practical experience. - 3+ years of experience as a Data Analyst, with proven ownership of end-to-end analysis and stakeholder delivery. - Experience in subscription business and/or acquisition-driven web funnels. - Strong experience in Product Analytics: funnels, cohorts, retention, LTV, churn, segmentation. - Proven hands-on experience designing, running, and validating end-to-end A/B tests - Hands-on experience with event analytics tools: Mixpanel, GA4, Amplitude, or similar - Advanced SQL - Experience with BI tools such as Tableau, Looker, or similar. - Strong analytical and problem-solving skills; ability to identify trends, patterns, and root causes in large datasets. - Excellent verbal and written communication; ability to translate analysis into clear business actions. - Ability to adapt quickly, learn new tools efficiently, and deliver high-quality work in a high-pressure, fast-changing environment. - Strong spoken and written English. NICE TO HAVES - Experience in Marketing Analytics - Experience with Python and/or R - Experience with GCP and BigQuery. - Experience with Google Ads, Meta/Facebook Ads, or other ad platforms. - Experience with orchestration frameworks such as Airflow and/or dbt. - Experience with Git and code review processes. - Experience with billing/payments analytics LOCATION Ruby Labs operates within the CET (Central European Time) zone. Applicants from any country are welcome to apply for the position as long as they are located within approximately ± 4 hours of CET. This ensures optimal collaboration and communication during working hours. BENEFITS Discover the perks of being part of our vibrant team! We offer: - Remote Work Environment: Embrace the freedom to work from anywhere, anytime, promoting a healthy work-life balance. - Unlimited PTO: Enjoy unlimited paid time off to recharge and prioritize your well-being, without counting days. - Paid National Holidays: Celebrate and relax on national holidays with paid time off to unwind and recharge. - Company-provided MacBook: Experience seamless productivity with top-notch Apple MacBooks provided to all employees who need them. - Flexible Independent Contractor Agreement: Unlock the benefits of flexibility, autonomy, and entrepreneurial opportunities. Benefit from tax advantages, networking opportunities, reduced employment obligations, and the freedom to work from anywhere. Read more about it here: https://docs.google.com/document/d/1nkrN76JlZkbKj9WSOhlT1_mni_CZeDkHdwfIjPXVwvk/preview?tab=t.0#heading=h.ndsdl4wapxtt Be part of our fast-growing team and seize this excellent opportunity for personal and professional growth! INTERVIEW PROCESS After submitting your application, we conduct a thorough review which typically takes 3 to 5 days, but may occasionally take longer due to the volume of applications received. If we see a potential fit, we proceed with the following steps: - Recruiter Screening (40 minutes) - Technical Interview (90 minutes) - Final Interview (60 minutes) LIFE AT RUBY LABS At Ruby Labs, we move fast, aim high, and expect the same from our team. We’re not here to play small—we’re here to build, grow, and win. That means we look for people who are ambitious, driven, and ready to give their best every single day. This is a place for individuals who thrive under pressure, embrace challenges, and see opportunity in every obstacle. If you’re hungry to achieve, motivated by impact, and want to grow at the speed of your own ambition, Ruby Labs offers the platform to make it happen. Here, effort is matched with reward. We recognize those who go all in and deliver results, and we create space for people who want more—more responsibility, more growth, and more success. #LI-Remote

Задачи: — Тестирование backend и ETL/ELT-процессов в Airflow: корректность загрузок, обработка ошибок и ретраи, идемпотентность; — Проверка качества данных, поиск потерь и дублей; — Тестирование OLAP-слоя: меры, измерения, производительность запросов, права доступа; — Тестирование интеграций с внешними системами через API и файловые обмены; — Проектирование тест-кейсов на основе архитектурной документации; — Автоматизация проверок и сверок данных на Python; — Работа с Jira, Confluence и TMS. Требования: — Официальный коммерческий опыт тестирования от 3,5-4 лет, преимущественно backend / data-систем; — Уверенный SQL: джойны, агрегации, оконные функции, работа с большими объёмами данных; — Опыт тестирования DWH и понимание принципов построения хранилищ данных; — Опыт работы с Airflow и понимание ETL/ELT-процессов; — Знание Python для автоматизации тестирования, сверок данных и анализа логов; — Опыт тестирования REST API; — Опыт работы с Jira / Confluence / TMS. Будет преимуществом: — Опыт работы в банковской или финансовой сфере; — Опыт тестирования AI/ML-компонентов; — Docker / Kubernetes. Условия: — Удаленный формат работы (в т.ч. вне РФ); — Оформление по ТК РФ в аккредитованную IT-компанию или по ИП; — ДМС со стоматологией с первого дня; — Предоставление техники на выбор; — Работа в сильной команде с возможностью обмена экспертизой; — Зарплата от 300 000 на руки.

Задачи: — Эксплуатация и тюнинг СУБД: полный контроль над состоянием, профилированием и оптимизацией PostgreSQL под конфигурацию серверов в AWS; — Настройка и сопровождение отказоустойчивости и HA/DR: репликация, Patroni, PgBouncer, бэкапирование и катастрофоустойчивость; — Проактивный мониторинг: поиск медленных запросов (pg_stat_statements, анализ планов выполнения), оптимизация индексов, помощь разработчикам; — Развитие в Data Engineering: участие в построении ETL-пайплайнов и работа со смежным стеком данных (до 60% задач в перспективе); — Автоматизация: написание скриптов для сбора метрик, диагностики и обслуживающих процессов на Python и Bash. Требования: — Опыт от 5 лет в роли экспертного PostgreSQL DBA в высоконагруженных продакшн-средах; — Глубокое понимание PostgreSQL: процессы, память, WAL, блокировки, тонкая настройка autovacuum под High-Load; — Практический опыт с отказоустойчивыми связками (Patroni, PgBouncer, потоковая репликация); — Опыт работы с PostgreSQL в облачной инфраструктуре AWS (EC2 / RDS); — Желание развиваться в Data Engineering (ETL, пайплайн-инструменты); — Английский язык от уровня B2 / Upper-Intermediate для устного общения. Будет плюсом: — Опыт работы с инструментами Data Engineering (Airflow, Python-пайплайны); — Навыки программирования на C; — Опыт проведения миграций и мажорных апгрейдов больших баз данных. Условия: — Достойный оклад ($6000–9000); — Возможность освоить Data Engineering на реальных больших данных с поддержкой ментора; — Стабильный и технически зрелый проект без «пожаров» и хаоса; — Гибкий график работы и высокая степень инженерной автономии.

Задачи: — Превращать телеметрию автономного транспорта в данные, удобные для анализа: разрабатывать и запускать Spark-пайплайны, продумывать преобразования и проверки качества — Подключать новые источники данных: разрабатывать интеграции с различными системами и обеспечивать надёжную загрузку данных в хранилище — Развивать архитектуру Data Lake / DWH — Вместе с командой формировать общие подходы к разработке, мониторингу и сопровождению пайплайнов Требования: — Практический опыт разработки и сопровождения пайплайнов данных — Опыт работы с PySpark, Python и SQL — Опыт работы с Data Lake / DWH и понимание принципов построения ETL/ELT-процессов — Понимание принципов распределённой обработки данных Будет плюсом: — Опыт работы с Trino+S3 — Опыт оркестрации пайплайнов с помощью Airflow — Знакомство с Data Vault 2.0 — Знание Scala и опыт её использования для обработки данных — Опыт развития платформы данных на ранних этапах: от выбора решений до их внедрения и сопровождения