Lead Data Architect

Lead/Principal Data Architect | Germany (Hybrid)

I’m partnered with a firm that has been turning engineering excellence into consistent growth for over five decades, generating strong revenue while maintaining technical integrity and independence. They are now looking to hire a Lead Data Architect.

You’ll architect cloud native data platforms on Azure and Databricks, including workspace separation, Unity Catalog integration, lakehouse and medallion structures, compute patterns, access models and cost-efficient orchestration. You’ll define engineering standards for PySpark processing, streaming, metadata management and CI/CD for data. You’ll also diagnose complex performance issues, advise on governance and shape the tooling that supports the full data lifecycle. Delivery happens in small teams of 1–10 people, so your decisions have real impact.

You bring 7 years in data or platform engineering and at least 2 years as a data architect. You’ve designed and delivered ETL and ELT pipelines, worked with large-scale distributed processing and understand how data platforms behave in production. You can code in Python/PySpark or are capable of reviewing, debugging and refactoring code to a high standard. Strong Java or Scala backgrounds are also welcome.

Expect:
• Architect platforms built on Fabric, Databricks Lakehouse and modern Azure or AWS services
• Influence ingestion and transformation patterns, schema evolution and Delta optimisation
• Lead decisions across compute patterns, cluster sizing, storage formats and table design
• Implement observability and reliability practices that scale under real workloads
• Work with strong engineering teams who expect technical leadership, not oversight
• Shape ML/AI infrastructure for model training, deployment and monitoring
• Solve the challenging edge cases internal teams typically avoid

German fluency is mandatory.

Hybrid in Germany across multiple locations.

If this feels like a good fit, send over your profile and we’ll take it from there.