Senior Data Engineer (m/f/d)

Scalable Data Pipelines: Design, build, and operate automated pipelines on Apache Airflow to transform largescale automotive datasets balancing and on schedule. PostgreSQL Ownership: Optimize our data platform through advanced SQL (CTEs, window functions), query plan analysis (EXPLAIN ANALYZE), indexing/partitioning strategies, and performance tuning under production load. AI-Driven Development: Proactively leverage AI tools and new technologies to amplify system scalability and stay of industry trends. Collaborative Modeling: Partner with analysts and data scientists to model data for the warehouse and downstream marts, translating business needs into high-quality data products. Python Tooling: Develop robust data services and processing tools in Python, emphasizing clean code, comprehensive testing, and maintainability. Strategic Architecture: Influence architectural decisions regarding specialized stores, batch vs. streaming tradeoffs, and the evolution of our technical ecosystem. Quality & Observability: Maintain a rigorous data quality framework, including freshness monitoring, SLA alerting, and end-to-end pipeline observability.

Completed university degree in Computer Science, Business Informatics, Mathematics, Statistics, or a comparable f ield. Several years of professional experience as a Data Engineer or in a closely related role, ideally working with substantial data volumes in production. Strong command of SQL, including the ability to read and interpret EXPLAIN ANALYZE and reason about query cost, indexes, and data layout. Solid hands-on experience with PostgreSQL in production: indexing strategies, partitioning, pg_stat_statements, vacuum/autovacuum tuning, replication, and an understanding of MVCC. Practical experience with Apache Airflow beyond writing DAGs: scheduler internals, executors, pools, XCom, idempotency, and deferrable operators. Confident Python developer (typing, testing, libraries search as pandas / Polars / SQLAlchemy). Experience with Git and CI/CD; comfortable working through code review and automated testing. Analytical mindset — the habit of measuring before optimizing, forming hypotheses, and verifying them with data. A professional, confident demeanor in client communication, paired with a structured, thorough, and independent way of working. Nice to Have Familiarity with columnar / analytical databases (ClickHouse, Snowflake, BigQuery). Exposure to CDC tools and streaming platforms. Experience using Docker, Rust, or Golang. Data quality frameworks and observability stacks (Prometheus, Grafana). Background in DWH design principles and cloud platforms (AWS, GCP, or Azure).

Open company culture: An open, team-oriented, and appreciative culture within a business, shaped by communication and transparency. Flexible working models: Family and career? No problem with us. Flexible working arrangements help you balance personal life and work in the best possible way. Ownership and authority: Real room for shaping decisions, with the opportunity to influence the future direction of the company. Training and development: Attractive opportunities for professional and personal growth, supported by targeted coaching and seminars. Career perspectives: A challenging role with diverse development paths — towards both leadership and technical specialization. On top: Corporate benefits, team events, and company celebrations. .