QA Engineer

• Data Engineers, BI Developers, Product Owners, Solution Architects to validate end-to-end data pipelines, data transformations, reporting solutions, and analytics applications.

Responsibilities : -

• Drive quality improvements through automation and process optimization.
• Collaborate with architecture, engineering, and business teams to define acceptance criteria and quality metrics.

Databricks Testing : -

• Validate data ingestion, transformation, and processing workflows built in Databricks.
• Test PySpark notebooks, Delta Lake implementations, and ETL/ELT pipelines.
• Validate Medallion Architecture layers (Bronze, Silver, Gold).
• Test data integrity across source and target systems.
• Perform reconciliation testing between upstream and downstream datasets.
• Conduct schema validation and data quality testing.

Power BI Testing : -

• Validate Power BI dashboards, reports, and semantic models.
• Test calculated columns, DAX measures, KPIs, and business metrics.
• Perform report regression testing after model changes.
• Validate row-level security (RLS) implementation.
• Verify drill-through functionality and report interactions.
• Ensure consistency between source data and visualized metrics.

Test Automation : -

• Develop comprehensive data quality test plans.
• Execute source-to-target reconciliation testing.
• Validate business rules and transformation logic.
• Identify root causes of data quality issues and work with engineering teams on remediation.
• Perform user acceptance support and release validation.