Top Data Engineer Jobs in Hamburg

As a Data Engineer at Zapier, you'll build scalable data systems, enhance product functionality through data, and collaborate with teams to improve data access and usability.

As a Data Engineer, build and manage data pipelines, ensure data quality, and support analytics for trading. Collaborate with teams to define data needs and best practices for infrastructure and applications.

As a Software Developer & Data Engineer, you'll develop software solutions, maintain web applications, administer Azure services, ensure software quality, and manage databases, contributing to maritime process optimization.

As a Data Engineer, you'll maintain and configure the Snowflake data platform, design integration pipelines, and innovate with new tools. Your role supports data security and performance while collaborating across teams.

The Junior Data Engineer will analyze data, design experiments, build a marketing data stack, and collaborate with teams to improve data access and insights.

The (Senior) Data Engineer designs and maintains data pipelines, collaborates with clients on data needs, and develops dashboards for insights.

As a Data Engineer at Nansen, you will build and optimize systems for their customer-facing analytics product, collaborating closely with crypto researchers and engineers to tackle large-scale data challenges and ensure data quality and reliability.

Responsible for developing backend AI features, integrating machine learning models, building data pipelines, and maintaining AI services within a retail ecosystem.

The Data Engineer will build scalable data pipelines, manage data transformations, and ensure data products align with business needs through collaboration.

The Principal Data Engineer will improve data pipeline architecture, optimize data flows, and support data projects for various teams in the company.

The Senior Data Engineer will design, build, and maintain data pipelines and infrastructure, ensuring data reliability and performance while collaborating with cross-functional teams to deliver data-driven solutions.

The role involves building and maintaining end-to-end data pipelines on AWS, ensuring data reliability, collaborating with teams, and staying updated with data engineering advancements.

Develop new features, review database changes, document best practices, and improve product performance in backend engineering focusing on data frameworks.

The Data Ops Engineer will design and build data pipelines, develop automated systems for insights delivery, enable AI workflows, and optimize data strategy.

The Python Data Engineer will design and implement data pipelines, build integrations, develop APIs, ensure CI/CD compliance, and mentor team members.

Design and architect scalable backend services, develop robust governance systems, build SaaS solutions, and mentor junior engineers to enhance IoT platform capabilities.

The Sr Data Engineer will enhance the DoiT Cloud Intelligence product, optimize big data warehouses, and collaborate with cross-functional teams to improve data models and systems.

As a Sr Data Engineer, you will improve data warehouse performance, collaborate on data models, and design monitoring tools.

The Sr Data Engineer will analyze and optimize big data warehouses, improve data models and pipelines, and design monitoring tools.

Lead validation and automation of data pipelines and ETL workflows, ensuring quality and reliability of data across cloud-native platforms. Collaborate with teams to implement automated testing and integrate quality checks into CI/CD pipelines.

The Senior Software Engineer in Test will validate and automate the quality of data pipelines and ETL workflows, ensuring data integrity and performance in a cloud-native SaaS platform.

Lead validation and automation of data pipelines, ensure data quality, and collaborate on building robust testing frameworks for cloud-native applications.

Lead validation and automation of data pipelines and ETL workflows, ensuring data quality and performance across cloud-native platforms. Collaborate with teams to maintain automated test frameworks and quality gates.

Lead validation and automation of data pipelines and ETL workflows, ensuring data integrity and performance across cloud-native platforms. Collaborate with teams to design, build, and maintain test frameworks, while mentoring peers and enhancing best practices in data testing and automation.

Design and maintain data pipelines, collaborate with stakeholders, ensure data quality, deploy infrastructure as code, and optimize reporting solutions.