Top Data Engineer Jobs in Germany

As a Senior Data Engineer, you will design scalable data pipelines, implement new technologies, collaborate with Data Scientists, and lead technical aspects while maintaining documentation on data processes.

Architect and build a greenfield data warehouse, develop resilient ETL/ELT pipelines, ensure data integrity, and lead junior engineers. Work on modern data infrastructure with a focus on AI integration.

The role involves creating and automating infrastructure features for data platforms using Python, with a focus on distributed systems and collaboration within a global team.

The role involves automating OpenSearch operations by developing features in Python, collaborating with an international team, and providing expertise on data platforms.

As a Software Engineer on the data platform team, you'll automate data platform operations, write Python code, and collaborate on solutions within a distributed team.

Build and operate a centralized Data Lakehouse: design and maintain end-to-end ELT/CDC pipelines with Databricks DLT, ensure data quality and governance via Unity Catalog, collaborate across teams, translate business needs into performant Lakehouse data products (Gold layer), and document best practices.

Design, build, and optimize large-scale batch and streaming ETL pipelines and ML infrastructure for real-time recommender systems. Implement high-throughput/low-latency data stores, ensure data governance and quality, collaborate with product, data science, and engineering teams, and influence architecture and team objectives to deliver measurable business impact.

Build and operate production machine-learning systems for financial-crime transaction monitoring. Responsibilities include developing batch training pipelines, engineering AML and fraud features, deploying and monitoring models, evaluating drift and performance, calibrating thresholds, conducting sensitivity tests, and producing governance documentation. The role partners with AML investigators, fraud operations, product, and engineering teams to deliver explainable, auditable, and scalable ML solutions.

Build and operate scalable data pipelines, ingestion integrations, dbt models, and orchestration on Snowflake, Airflow, and Azure. Define data platform architecture, developer tooling, infrastructure-as-code, governance, observability, testing, privacy controls, and engineering standards. Lead technical decisions, roadmap development, stakeholder collaboration, and self-service enablement for analytics and business teams.

Lead mechanical design for data centre projects, manage teams, engage clients, mentor junior engineers, and incorporate industry advancements.

The Associate Director will lead mechanical design for data centres, manage project delivery, engage with clients, mentor junior engineers, and stay updated on industry trends.

The Associate Director will lead mechanical engineering design for data centre projects, manage project delivery, and mentor junior engineers while ensuring client satisfaction and incorporating innovative solutions.

Lead design, implementation, and operation of scalable data pipelines and platform infrastructure on AWS. Define data quality, observability, and operational controls; evolve analytics (ClickHouse, Metabase); build pipelines with Python (pandas, polars), dbt, and dlt; drive cross-team initiatives, mentor engineers, and improve platform reliability and developer experience.

Join Zencore as a Senior Data Engineer, leveraging Google Cloud expertise and technology strategies to assist clients with data and application modernization.

Lead design and build of high-throughput Reverse ETL and data pipelines, modernize pipeline architecture, choose appropriate storage and data models (MySQL, ClickHouse, OpenSearch, BigQuery), drive observability and reliability (Datadog), collaborate with backend and analytics engineers, and set engineering standards to scale sponsored content and CPC marketplaces.

Lead technical direction and architecture for the data platform, mentor a team of engineers, own data infrastructure (lake, foundations, semantic layer, governance), drive streaming adoption, apply strong data modeling, and collaborate with product and engineering stakeholders to enable AI-powered analytics and a self-service data platform.

Lead technical direction and architecture of the data platform, mentor a team of 4–5 engineers, evolve data infrastructure (lake, semantic layer, governance), drive streaming adoption, data modeling, and self-service platform practices while collaborating with product and cross-functional stakeholders.

Lead technical direction and architecture of the data platform, mentor a team of 4-5 engineers, own data infrastructure (lake, foundations, semantic layer, governance), drive streaming adoption, advance data modeling, and collaborate with product and engineering stakeholders to enable AI and analytics features.

Lead architecture and implementation of real-time data pipelines and dynamic tables at cloud scale. Drive technical strategy, resolve systemic bottlenecks, mentor senior engineers, run design reviews, partner with product and infrastructure, and deliver hands-on work in streaming ingestion and incremental processing.

Lead design and implementation of client study standards aligned to CDISC (SDTM/ADaM) and regulatory guidance. Provide guidance, training, mentorship, and governance support; partner with statisticians and programmers to build tools and metadata repository solutions; ensure submission readiness and represent IQVIA in industry standards initiatives.

Lead the design and scaling of dbt data models and ETL/ELT pipelines, translate business needs into analytics, coordinate delivery, mentor team members, and optimize data workflows for reliability and scalability.

The Software Engineer will manage data collection and processing to enhance AI model training, collaborating with scientists and extending cloud infrastructure.

The Software Engineer will support data collection for AI model training by enhancing the ingestion pipeline, collaborating with scientists, and managing cloud infrastructure.

Design and scale mission-critical market data services for stocks, options, crypto, and foreign exchange. Responsibilities include architecting backend systems and APIs, maintaining software quality and test coverage, participating in code reviews, and troubleshooting incidents and bugs. The role uses Go and Python with REST, gRPC, WebSockets, SSE, Docker, Kubernetes, Google Cloud, BigTable, Prometheus, Grafana, and ELK.

The Senior Data Engineer will design and build data pipelines on GCP, ensuring high data quality and reliability for analytics and ML products. Responsibilities include mastering ETL processes, managing workflows with Airflow, and collaborating closely with ML engineers.