Data Engineer – Azure Data Platform

• Hands-on experience with:
  • Azure Data Factory
  • Microsoft Fabric (Lakehouse, Warehouse, OneLake)
  • ETL/ELT pipeline design and development
• Strong knowledge of Power BI, including:
  • Power BI Service and licensing
  • DAX
  • Power Query (M language)
  • Row-Level Security (RLS)
  • Semantic models and dataset refresh scheduling
• Experience with data pipeline orchestration, monitoring, and troubleshooting
• Knowledge of working with secure data access and credentials (e.g., Azure Key Vault)
• Experience with configuring data integration between cloud and on-prem environments
• Familiarity with GCP services (Cloud Storage, Cloud SQL)

Nice to have

• Experience working in the banking or financial services sector
• Knowledge of additional cloud data services or scripting (e.g., Python)

Location: Kraków (Hybrid – 6–8 days per month in the office)
Contract type: B2B or Employment Contract (via Antal)

About the role

We are looking for an experienced Data Engineer to join a data platform team delivering modern data solutions within a cloud-based ecosystem. You will be responsible for building scalable data pipelines and supporting analytics capabilities using Azure and Power BI technologies.

This role combines data engineering with elements of cloud and BI, offering exposure to modern platforms such as Microsoft Fabric.

What we offer

• Long-term cooperation (B2B or UoP via Antal)


• Opportunity to work with modern data platforms (Azure + Microsoft Fabric)


• Involvement in projects within the banking sector


• Hybrid work model with flexibility

,[Design, build, and maintain ETL/ELT data pipelines using Azure Data Factory and Microsoft Fabric (Lakehouse / Warehouse, OneLake), Develop and optimize data ingestion and transformation processes (including incremental loads), Ensure secure data access and management of secrets using Azure Key Vault, Configure and maintain on-premises data gateways, Monitor pipeline performance and implement error-handling and recovery mechanisms, Support orchestration and scheduling of data workflows, Collaborate with analytics teams on data models and reporting layers] Requirements: Azure, Azure Data Factory, Microsoft Fabric, Lakehouse, Warehouse, OneLake, ETL, ELT pipeline, Power BI, DAX, Power Query, RLS, Semantic models, Data pipelines, Azure Key Vault, GCP, Cloud Storage, Cloud SQL, Banking, Financial services sector, Cloud data services, Scripting, Python