Data engineer

We are launching a strategic data transformation initiative to replace our legacy SAS and Exadata-based environment with a modern Microsoft Fabric-powered Data & Analytics platform. We are seeking a skilled Data Transformation Engineer to join our team and play a key role in this transformative project. The successful candidate will be responsible for migrating data integration flows, data warehouses, reports, dashboards, data products, and advanced analytics and machine learning solutions while ensuring continuity of business operations.

• Participate in the implementation and configuration of the Microsoft Fabric Data & Analytics platform, supporting data integration, analytics, and reporting initiatives.
• Develop and maintain data pipelines, transformation processes, and data models as part of the migration from SAS and Exadata environments.
• Assist in the migration and validation of reports, dashboards, data marts, data products, and analytical workloads to the target platform.
• Collaborate with business users and technical teams to gather requirements, troubleshoot issues, and ensure successful delivery of data solutions.
• Support the implementation of data quality controls, metadata management, catalog, and glossary processes in accordance with governance standards.
• Perform testing, documentation, and operational support activities to ensure platform reliability and data accuracy.
• Contribute to performance optimization, automation, and continuous improvement of data and analytics solutions.
• Participate in knowledge transfer activities and provide ongoing support during migration and post-go-live phases.

• Certification in the data transformation technology - MS Fabric
• Fabric Dataflows Gen2, Data Factory pipelines, Notebooks (PySpark)
• Delta Lake table creation, partitioning, and maintenance
• OneLake storage management (hot/cold tier data movement)
• Batch ingestion (full load, incremental, CDC)
• Real-time ingestion (Fabric Real-Time Intelligence, Event Hub)
• API and webhook ingestion
• PySpark transformation development (Bronze → Silver → Gold)
• SQL transformation logic (Fabric Warehouse, dbt)
• Data cleansing and standardisation logic
• Azure DevOps Git workflow (feature branch, PR, merge)
• Automated unit test development (dbt tests, Great Expectations)
• Pipeline monitoring and alerting configuration
• Data lineage tag propagation (Purview auto-lineage)
• Fluent communication skills in English and Polish (minimum B2 level), both written and spoken.

• Hybrid work model: 2 days from the office, 3 days of home office.