Data engineer for SaaS products

team.blue; United States; Remote; USD 120,000 - 190,000; Full time

Job summary

team.blue — экосистема брендов, работающих вместе, ищет Senior Data Engineer для разработки и поддержки центральной data экосистемы, обеспечивая максимальную стратегическую ценность глобальных данных.

Ключевые задачи включают владение платформой данных, разработку масштабируемых data products и пайплайнов ETL/ELT, архитектурное лидерство и соблюдение данных, сотрудничество с командами Analytics/ML. Требуется 7+ лет опыта и продвинутые знания SQL, Databricks, AWS/Cloud, Airflow.

Qualifications

• 7+ лет опыта в data engineering или data management.
• Опыт работы с Databricks PySpark, Delta Lake и Unity Catalog.
• Опыт работы в облачных средах (AWS или GCP) и с Airflow/dbt.
• Умение вести проекты и наставлять команду.

Responsibilities

• Владение Data Platform и оптимизация инфраструктуры Databricks, Airflow, dbt, AWS.
• Разработка масштабируемых data products и единого источника правды.
• Построение ETL/ELT конвейеров с высокой доступностью.
• Архитектурное лидерство, управление данными и метаданными.
• Взаимодействие с аналитикой, ML и AI командами.
• Оптимизация платформ, индексация и эволюция схем.

Skills

Databricks PySpark

Delta Lake

SQL продвинутый

Data modeling

Облачные решения (AWS)

Airflow

dbt

Docker

Kubernetes

CI/CD

Education

Масштабный диплом в Computer Science/ STEM

Tools

Databricks

GitLab

Unity Catalog

Delta Lake

Job description

Описание: team.blue is an ecosystem of successful brands working together across regions to provide customers with everything they need to succeed online. 60+ successful brands make up the group; with a team of more than 3000+ experts serving its 3.5 million customers across Europe and beyond. As a Senior Data Engineer, you will develop and maintain our central data ecosystem, ensuring we extract maximum strategic value from our global data assets.

Задачи:

• Data Platform Ownership: Own, manage, continuously optimize our Data Infrastructure including Databricks, Airflow, dbt, Gitlab & AWS. Manage and tune data platforms for peak performance and introduce new capabilities to keep the platform aligned with industry advancements
• Data Product Innovation: Design and deliver high-quality, scalable data products that provide a unified source of truth across a complex ecosystem of 60+ global sub-brands.
• Pipeline Engineering: Build and optimize robust ETL/ELT pipelines to ingest and transform massive volumes of structured and unstructured data, ensuring high availability and low latency for downstream consumers.
• Architectural Leadership: Lead the design of secure, cost-efficient data architectures. Establish and enforce best practices in data modeling, orchestration, and observability.
• Governance & Integrity: Implement rigorous data governance frameworks, including lineage tracking, metadata management, and quality controls to ensure a reliable semantic layer for AI and ML use cases.
• Cross-Functional Collaboration: Act as a strategic "sparring partner" for Analytics, ML, and AI teams, translating complex business requirements into high-performing technical solutions.
• Platform Optimization: Manage and tune data platforms for peak performance, focusing on indexing strategies, query optimization, and schema evolution.
• Mentorship: Elevate the collective expertise of the engineering team by mentoring junior members and fostering a culture of technical excellence.

Требования:

• Strategic Thinker: You don't just execute; you lead projects from ideation to actionable solution, balancing technical debt with rapid delivery.
• Effective Communicator: You possess the ability to translate complex technical concepts into clear business value for non-technical stakeholders.
• Problem Solver: You thrive in fast-paced environments, managing multiple high-priority workstreams with meticulous attention to detail.
• Core Ecosystem: Deep hands-on experience with Databricks (PySpark, Delta Lake, Unity Catalog).
• Advanced SQL & Modeling: Expert-level SQL skills (optimization, indexing) and a mastery of data modeling techniques (Dimensional, Star Schema, Snowflake).
• Cloud & Modern Data Stack: Proficiency in at least one major cloud provider (AWS, GCP, etc) and modern orchestration tools like Airflow or dbt.
• Database Diversity: Proven experience managing data across various RDBMS platforms (PostgreSQL, SQL Server, Oracle, etc.).
• DevOps & Engineering: Strong command of Docker/Kubernetes and a commitment to CI/CD best practices.
• Governance: Experience with data versioning, schema evolution, and distributed metadata management.
• Experience: 7+ years of professional experience in data engineering or data management, preferably within a high-growth or multi-brand industry.
• Education: Advanced degree (Masters or PhD) in Computer Science, STEM, or a related quantitative field.
• Track Record: A demonstrable history of deploying stable, high-performance data solutions that drive measurable business value.
• At any stage, please be prepared to provide proof of eligibility to work in the country you’re applying for.

Условия:

Unfortunately, we are unable to support relocation packages or sponsorship visas