Top Data Engineer Jobs in Germany

End-to-end delivery of ML-powered services, involving research, prototyping, production, and operations. Collaborate on product requirements while maintaining high quality and operational excellence.

As a Senior Data Engineer, you'll build scalable solutions for the Data Platform, develop ETL processes, ensure data quality, conduct data modeling, and guide junior engineers.

Design and develop a platform to enhance simulation and stellarator design processes, manage cloud infrastructure, and improve DevOps practices.

As a Software Engineer, you will develop and optimize real-time data pipelines for athlete tracking, ensuring high-performance software solutions for sports analytics.

Design and implement search retrieval and ranking systems, build data pipelines, and evaluate performance metrics. Collaborate with teams to enhance system relevance.

As a Data Platform Engineer, you will design, build, and maintain a cloud data platform, ensuring its reliability and efficiency while supporting AI integration and collaboration with internal teams.

Design and validate cloud data, analytics, and GenAI/RAG architectures; lead customer discovery, craft solution designs and PoCs, deliver demos, and communicate technical value to stakeholders.

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

The Senior Data Engineer will design scalable systems, automate ML operations, optimize performance, and enhance infrastructure for data processing and monitoring.

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

The role involves maintaining EUMETSAT Copernicus software, correcting anomalies, optimizing performance, and documenting the code while working collaboratively in a team.

The DevOps Engineer will maintain application environments, ensure infrastructure availability, oversee deployment processes, and lead training sessions within the team.

Build and operate Python/PySpark production data pipelines (including near real-time), ensure data quality, create core data models and reporting pipelines for AML/Risk, support regulatory reporting and data governance, and collaborate with cross-functional teams to deploy scalable, auditable data solutions.

Design and build reliable, performant data pipelines for large payment datasets. Own end-to-end data flows, drive data quality, implement transformations (dbt), operate on StarRocks and Flink/Spark in cloud (AWS/GCP), collaborate cross-functionally, establish engineering standards, mentor engineers, and shape CI/CD and incident practices.

The Senior Data Engineer designs, maintains, and optimizes ML applications and data pipelines, ensuring compliance and quality while mentoring junior engineers.

As a Senior Data Engineer, you will design and maintain ML applications, manage workflows, build data pipelines, and mentor junior engineers within a global team.

Design and maintain data infrastructure, build pipelines for data collection, ensure data quality, and collaborate with stakeholders on data requirements.