Lead Data Architect

Trust In SODA; Dortmund; Hybrid; EUR 90.000 - 120.000; Vollzeit

Zusammenfassung

A leading technology firm is seeking a Lead Data Architect in Germany (Hybrid) to architect cloud native data platforms leveraging Azure and Databricks. The ideal candidate will have over 7 years of experience in data engineering, a strong grasp of data architecture principles, and proficiency in Python or PySpark. The role requires strong problem-solving skills, technical leadership, and the ability to influence engineering practices across diverse teams. Fluency in German is mandatory for this position.

Qualifikationen

• 7+ years in data or platform engineering.
• At least 2 years as a data architect.
• Experience designing ETL and ELT pipelines.

Aufgaben

• Architect cloud native data platforms on Azure and Databricks.
• Define engineering standards for data processing.
• Diagnose complex performance issues.

Kenntnisse

Data architecture

Python

PySpark

Java

Scala

Cloud native infrastructure

Tools

Azure

Databricks

Fabric

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.