Role Overview :

We are looking for an experienced Microsoft Fabric & Power BI Data QA / Test Engineer with strong expertise in end-to-end data testing, SQL, PySpark, Microsoft Fabric, and Power BI testing. The candidate will be responsible for validating data pipelines, transformations, semantic models, DAX calculations, dashboards, and reporting accuracy across the complete analytics lifecycle.

Key Responsibilities :

- Develop and execute end-to-end test strategies and test plans for data and BI solutions.

- Validate data ingestion, transformations, incremental loads, watermarking, schema changes, and source-to-target mappings.

- Test Microsoft Fabric components including OneLake, Lakehouse, Data Warehouse, Data Pipelines, Dataflows Gen2, and Notebooks.

- Perform comprehensive Power BI testing, including semantic models, DAX measures, KPIs, slicers, visual interactions, and Row-Level Security (RLS).

- Reconcile Power BI metrics against Fabric Lakehouse/Warehouse and source-system data.

- Develop complex SQL queries for data validation, reconciliation, aggregation, and regression testing.

- Use PySpark/Python for automated data-quality checks and large-volume data validation.

- Validate pipeline error handling, retry mechanisms, and schema-drift scenarios.

- Identify, document, and track defects using Jira or Azure DevOps.

- Participate in Agile ceremonies including sprint planning, refinement, estimation, and retrospectives.

- Support integration of automated quality checks into Azure DevOps/CI-CD pipelines.

Mandatory Skills :

- 3 - 8 years of experience in Data QA / Data Testing / BI Testing.

- Hands-on experience with Microsoft Fabric (OneLake, Lakehouse, Data Warehouse, Data Pipelines, Dataflows Gen2, Fabric Notebooks).

- Strong hands-on Power BI testing experience.

- Strong SQL skills for complex validation and reconciliation.

- Hands-on PySpark / Python experience.

- Strong understanding of DAX, semantic models, relationships, cardinality, KPIs, and RLS.

- Experience with ETL/ELT testing and dimensional data modeling.

- Knowledge of Star and Snowflake schemas.

- Experience with Jira/Azure DevOps and Git.

Good-to-Have Skills :

- Great Expectations, PyTest, or other automated data-quality/BI testing frameworks.

- Azure Data Factory, Azure Data Lake, and Synapse Analytics.

- Certifications : DP-600, PL-300, or DP-203.