Data Engineer Microsoft Azure (m/w/d)

• Design, build, and maintain scalable data pipelines using Azure Data Services, Databricks and/or Microsoft Fabric.
• Consolidate structured/unstructured data into governed lakes and warehouses for BI and AI use cases.
• Implement robust data models and storage architectures (Star, Snowflake, Medallion).
• Ensure data integrity and quality, lineage, security, and governance across the full lifecycle.
• [Optional] Automate workflows using Azure DevOps, GitHub Actions, or other CI/CD tools.
• Collaborate in client workshops, translating requirements into technical Azure-native solutions.
• Optimize performance and cost efficiency of the data infrastructure.

 

Example Use Cases You Will Work On:

• Modernize legacy ETL workflows with Azure-native services.
• Build semantic models for enterprise BI using Star/Snowflake schema.
• Design medallion-structured ingestion flows to enable batch or near-real-time analytics.
• Deliver curated, governed data products for BI and AI use cases.

Must-Haves:

• 3+ years of real-world project experience as a Data Engineer in Azure ecosystems.
• fluent in german and english
• Advanced SQL and performance tuning.
• Strong background in dimensional data modeling and familiarity with ETL patterns, like medallion architecture.
• Hands-on experience with Azure Data Factory, Synapse, Databricks, and ideally Microsoft Fabric.

Nice-to-Haves:

• Proficiency in Microsoft Power BI.
• Exposure to Data Mesh or domain-oriented data architectures.
• Experience with Delta Lake, Unity Catalog, or Feature Store.

Soft Skills

• Strong communication and documentation skills (German & English).
• Agile, delivery-oriented mindset.
• Collaborative and self-directed approach.
• Analytical thinking with a focus on value delivery.
• Ability to translate business requirements into technical solutions.
• Experience working in agile, cross-functional teams.

You will be part of a collaborative, remote-friendly team that values continuous learning and
delivering impact through modern cloud-native data solutions.