Top Data Engineer Jobs in Germany

Designs and implements security frameworks for Snowflake and cloud data platforms across GCP and Azure. Automates infrastructure provisioning and security configurations with Terraform, manages GitHub Actions CI/CD security, and optimizes security solutions for threat detection and response. The role requires enterprise data protection, access control, DLP, DevSecOps, SIEM, cloud security, programming, documentation, and cross-functional collaboration with internal teams and vendors.

As a Senior Data & AI Engineer, you'll advise clients on data and AI solutions, analyze requirements, design tailored data solutions, and collaborate with project teams to deliver results.

As a Lead Data Engineer, you will design, build, and maintain scalable data platforms, assess data landscapes, and collaborate with stakeholders to translate requirements into robust data solutions.

Design and maintain data warehouse systems, develop ETL pipelines, manage datasets for analytics, and implement real-time data solutions.

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 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.

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

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.

Build and maintain scalable, reliable data infrastructure and self-service features for ETL, orchestration, and real-time analytics. Optimize compute and costs, automate operations for high availability, and contribute to designing and implementing new platform services.

Design and implement security frameworks for data platforms (Snowflake, GCP, Azure); automate infrastructure and security via IaC; manage CI/CD (GitHub Actions/Runners); integrate and operate SIEM and detection tools; collaborate with cross-functional teams and vendors; document processes and ensure compliance.

Design and implement security frameworks for enterprise data platforms (Snowflake, GCP, Azure). Automate infrastructure provisioning and security configs with IaC/Terraform, manage CI/CD via GitHub Actions, integrate security tooling and SIEM for threat detection, and document operational workflows while collaborating with cross-functional teams and vendors.

Design, implement, and maintain Python backend services and CI/CD/GitOps pipelines on AWS/Kubernetes. Build and maintain data models (Avro, SQL), publish via Kafka and schema registry, create access-layer models in Snowflake, and coordinate between Data and Tech teams to align schemas, priorities, and timelines.

Build and maintain ML-scale data infrastructure: feature store, real-time and batch pipelines, data quality and validation, and low-latency systems. Translate Data Science needs into high-performance Flink streams, eliminate ETL bottlenecks, collaborate on online ML systems, and implement monitoring, governance, and deployment processes for production ML workflows.

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

Leading and mentoring a data platform engineering team while overseeing platform architecture, development, and compliance with security and governance in a cloud environment.

Design, build, and maintain scalable ETL pipelines and data models for robotics; ensure data quality, governance, and security; develop streaming and dataset curation workflows; integrate modern data technologies; collaborate across teams to deliver high-quality datasets.

As a Senior Software Engineer, you'll design and build scalable market data systems, improve API architecture, and enhance overall system performance, contributing to Alpaca's infrastructure for trading financial assets.

As a Senior Data Engineer, you'll build and manage data pipelines, ensure data quality, and collaborate across teams, contributing to the Data Platform's growth.

Lead technical vision and architecture for enterprise data platforms. Own end-to-end platform design from ingestion to distribution, set engineering standards, mentor senior engineers, and collaborate with security, compliance, product, and stakeholders to deliver scalable, reliable, and compliant data platform capabilities.

Design, build, and operate scalable data infrastructure on AWS and Kubernetes. Develop streaming and platform components (Kafka, Snowflake), implement IaC (Terraform) and CI/CD (GitLab), build monitoring/observability, own features end-to-end, collaborate with analysts and data scientists, and participate in on-call rotations to ensure platform reliability and performance.