Azure Databricks Data Engineer
Hybrid · Stockholm, Stockholm, Sweden
Job Summary
Azure Databricks Data Engineer to design, build, and maintain scalable batch and streaming pipelines using bronze/silver/gold architectures; develop reusable transformation frameworks and production-grade Spark workloads; implement and optimize Delta Lake solutions with ACID, partitioning, schema evolution, OPTIMIZE/ZORDER, and CDC; manage Unity Catalog governance, permissions, lineage, and auditability; perform Spark performance tuning and observability; integrate Databricks with Azure services (ADLS, ADF/Synapse, Key Vault, Entra ID); implement CI/CD pipelines using Azure DevOps or GitHub Actions; collaborate with architects, analysts, data scientists, and engineers to align technical implementation with business needs; continuously improve platform performance, reliability, cost efficiency, and standardization.
Required Qualifications
- Strong hands-on expertise with Azure Databricks engineering
- Advanced Apache Spark experience using:
- PySpark or Scala
- Spark SQL
- Deep understanding of Delta Lake architecture and optimization techniques
- Experience building scalable enterprise data platforms and real-time pipelines
- Strong governance and security experience in multi-team environments
- Experience with service principals, managed identities, lineage, and auditability
- Strong troubleshooting and Spark performance optimization skills
- Azure integration experience across storage, orchestration, and security services
- Solid CI/CD and Infrastructure-as-Code exposure
- Comfortable working independently in consulting-style delivery environments
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