Lead Data Architect

Trust In SODA; Stuttgart; Hybrid; EUR 80.000 - 110.000; Vollzeit

Zusammenfassung

A leading data solutions firm is seeking a Lead Data Architect to drive the design of cloud native data platforms on Azure and Databricks. The role involves defining engineering standards for data processing, diagnosing performance issues, and shaping tooling for the data lifecycle. Candidates should have over 7 years in data engineering and a strong command of cloud technologies. German fluency is a must. This position is hybrid, allowing flexibility across multiple locations in Germany.

Qualifikationen

• 7+ years in data or platform engineering required.
• Minimum 2 years in a data architect role.
• Fluent in German.

Aufgaben

• Architect cloud native data platforms on Azure and Databricks.
• Define engineering standards for PySpark processing and CI/CD.
• Diagnose performance issues and advise on governance.

Kenntnisse

Data platform engineering

Python/PySpark programming

SQL

Java

Scala

Cloud-native architecture

Tools

Azure

Databricks

Jobbeschreibung

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.