• Develop comprehensive test strategies, test plans, test cases, test scripts and test execution reports.
• Execute software and data testing including functional, end-to-end, data migration quality assurance, regression and UAT support to ensure flawless system performance and data integrity.
• Lead end-to-end QA activities throughout the Software Development Life Cycle (SDLC) and Agile methodologies.
• Test ETL/ELT pipelines developed using Databricks and cloud-based data processing frameworks, requiring hands-on experience validating Delta Tables, Notebooks,SQL and PySpark transformations.
• Ability to prepare mock data sets as required for testing scenarios.
• Verify data quality checks within ingestion and transformation pipelines.
• Perform source-to-target reconciliation with Data Migration Testing experience
• Perform report reconciliation between legacy reporting systems and new analytics platforms.
• Prepare QA metrics, test status reports and release readiness assessments.
• Improve test coverage through automation and shift-left testing practices.
• Verify KPI calculations, measures, aggregations, filters and drill-down functionality.
• Ensure complete traceability between business requirements and testing artifacts.
• Conduct Root Cause Analysis (RCA) for defects and collaborate with development teams for resolution.
• Drive defect lifecycle management using tools such as Jira, Azure DevOps or Quality Center.
• Manage defect lifecycle and coordinate issue resolution with development teams.
• Integrate automation testing within CI/CD pipelines using Jenkins, Azure DevOps or GitHub Actions.
• Participate in sprint ceremonies and release validation activities.
• Experience with Master Data Management and one or more tools like Azure DevOps, Jira, Quality Center

Mandatory Skills:

ETL/Data Testing, Data Validation and reconciliation, Strong analytical & troubleshooting skills, Hands-on exposure to validating data across enterprise ETL platforms (AbInitio, SSIS, DataStage) and automating data quality checks using Pytest or similar testing frameworks.

Good-to-Have Skills:

• Healthcare Domain Experience with Healthcare Reporting & Analytics, Provider Data Validation,Clinical Data Testing, Claims Data Validation and understanding of Databricks ecosystem
• Experience working on large-scale cloud data migration, modernization or data warehouse transformation programs.
• Ability to understand complex data workflows and troubleshoot issues within data pipelines.
• Knowledge of cloud based data platforms such as Azure or AWS.
• Strong understanding of Agile Scrum Methodologies and proactive approach towards identifying risks and quality improvements.