Top Data Engineer Jobs in Germany

Own, design, and develop the AI Data Platform: maintain a high-scale data product platform (≈400K pipeline jobs/month, petabyte scale), architect cross-cloud data infrastructure, build and operate automated data pipelines, ensure data observability and quality, and implement AI-driven features and AI data agents to expose AI-ready data products.

Build and operate large-scale data pipelines and orchestration for generative AI research, focusing on video/audio datasets, feature extraction, labeling, and dataset quality to improve model performance.

Design and develop cloud-native backend services in Rust to process terabytes of data daily. Build and operate data-intensive microservices on AWS and Kubernetes, integrate with distributed databases and messaging systems (Kafka/RabbitMQ), and collaborate across teams to deliver observability features.

Develop backend services using Rust for cloud-native systems processing terabytes of data. Contribute to innovation in observability solutions.

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.

Own and harden the platform: tune HikariCP/ProxySQL/XtraDB connection paths, eliminate DB locking in JobRunr/Quartz queues, optimize Hibernate/JPA usage, manage Kubernetes availability and graceful shutdowns, instrument observability with Prometheus/Grafana, and plan migration to high-throughput messaging (NATS/RabbitMQ/Redis).

The Senior Data Platform Engineer will enhance the data platform infrastructure, collaborate with teams, implement infrastructure-as-code, optimize workloads, build CI/CD pipelines, and ensure observability and monitoring.

The Senior Data Platform Engineer will lead project delivery for data infrastructure, manage near real-time services, and collaborate across teams while contributing to AI and data governance frameworks.

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.

Design, build, and maintain scalable batch and real-time data pipelines; evolve the warehouse/lakehouse architecture for performance and reliability; implement data quality, monitoring, and observability; collaborate with Product, Analytics, Operations, and Engineering; take end-to-end ownership of data initiatives and optimize processing efficiency, query performance, and cost.

Own and transform supply data into governed, analysis-ready datasets. Build and monitor GCP/Python pipelines, optimize SQL, document schemas/lineage, manage access and costs, ensure data validity, and mentor analysts while aligning stakeholders on data contracts.

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.

Lead development of Data and AI features from data architecture to optimization and simulation. Design scalable data architectures, reliable pipelines, and DataOps/DevOps workflows. Partner with analysts, product managers and supply chain specialists to turn complex logistics data into actionable solutions.

Design, build, and operate large-scale distributed data systems and real-time/batch data pipelines. Collaborate with product, infrastructure, and data science teams, contribute to architecture and roadmaps, and write clean, tested production-quality code.

Design, build, and operate scalable real-time and batch data processing systems. Own features end-to-end, make architectural decisions, ensure production reliability and observability, collaborate cross-functionally, write high-quality tested code, and mentor junior engineers.

As a Senior Data Engineer, you will build and optimize data platforms and pipelines, ensuring the smooth transfer of terabytes of data and delivering critical reports for executive decisions.

The Technical Privacy Expert will implement privacy-by-design principles, ensure compliance with regulations, mentor teams, and develop technical frameworks for privacy in technologies.

Design, build, and optimize production-grade data pipelines and architectures. Implement DataOps practices, automate workflows, improve data quality, and collaborate with Data Scientists and stakeholders to deliver scalable cloud data solutions.

As a Software Engineer, analyze and process real-time athlete data to enhance performance and reduce injury risks, developing algorithms and optimizing data pipelines.

As a Senior AI Engineer, you will design and maintain data pipelines, curate datasets, ensure data quality, and run experiments to improve model outcomes, particularly for German-language data.

Build and operate production-grade data, evaluation, and observability infrastructure for LLM agents. Implement online/offline evaluation, quality gates, data pipelines, trace analysis, retention and replay, and observability tooling while working inside the backend and agent architecture to improve reliability, performance, and cost.

Build and operate Kafka and CDC pipelines, help architect an Iceberg-backed Lakehouse, deliver scalable data serving layers, enable self-service analytics, drive data observability, and consult teams on integration, modelling, and schema design.

Drive the complete tape-out flow including DGS database integration, mask data preparation, and DfX co-integration for graphene photonic platforms.

Own and evolve a GCP-native data platform from ingestion to reporting. Lead architecture, reliability, observability, data quality, cost optimization, and AI-assisted engineering practices while mentoring engineers and collaborating with product and customer teams.