Senior QA Engineer

Role Overview: As a Senior QA Engineer with 7+ years of experience, you will play a crucial role in ensuring the quality and integrity of data within Microsoft Fabric, specifically focusing on Data Engineering and Notebook Validation. Your expertise in Microsoft Fabric, PySpark, Spark SQL, and data validation frameworks will be instrumental in validating data pipelines, supporting data migrations, and designing automated validation processes. Key Responsibilities: - Perform end-to-end validation of data pipelines within Microsoft Fabric, including OneLake, Lakehouse, and Fabric SQL endpoints. - Test Bronze, Silver, and Gold data layers for completeness, accuracy, and transformation integrity. - Collaborate with Data Engineers to validate transformation logic and incremental load processing. - Develop and execute validation logic within Fabric notebooks using PySpark and Spark SQL. - Build reusable notebook-based validation frameworks and log validation results into Delta tables for auditability. - Validate data migrations to Microsoft Fabric from legacy platforms and perform before-and-after data comparison. - Design and implement automated validation frameworks for data pipelines and support CI/CD integration. - Work closely with Data Engineers, BI Developers, and Business Analysts to ensure data quality and provide QA sign-off for production releases. Qualification Required: - 7+ years of experience in Data QA, ETL Testing, or BI/Data Engineering validation. - Strong hands-on experience in Microsoft Fabric, PySpark, and Spark SQL. - Experience supporting data migration projects and strong SQL skills for backend data validation. - Understanding of data quality principles such as Accuracy, Completeness, Consistency, and Timeliness. - Experience in designing or implementing QA automation in data platforms. - Exposure to CI/CD pipelines and DevOps integration for data testing. Additional Details: The company focuses on successful validation of Fabric migrations with zero critical data defects, implementing automated notebook-based data validation frameworks, reducing manual data testing efforts through automation, and ensuring high confidence in data accuracy across reporting and analytics layers. Note: Preferred qualifications, key technical skills, and success criteria have been omitted for brevity. Role Overview: As a Senior QA Engineer with 7+ years of experience, you will play a crucial role in ensuring the quality and integrity of data within Microsoft Fabric, specifically focusing on Data Engineering and Notebook Validation. Your expertise in Microsoft Fabric, PySpark, Spark SQL, and data validation frameworks will be instrumental in validating data pipelines, supporting data migrations, and designing automated validation processes. Key Responsibilities: - Perform end-to-end validation of data pipelines within Microsoft Fabric, including OneLake, Lakehouse, and Fabric SQL endpoints. - Test Bronze, Silver, and Gold data layers for completeness, accuracy, and transformation integrity. - Collaborate with Data Engineers to validate transformation logic and incremental load processing. - Develop and execute validation logic within Fabric notebooks using PySpark and Spark SQL. - Build reusable notebook-based validation frameworks and log validation results into Delta tables for auditability. - Validate data migrations to Microsoft Fabric from legacy platforms and perform before-and-after data comparison. - Design and implement automated validation frameworks for data pipelines and support CI/CD integration. - Work closely with Data Engineers, BI Developers, and Business Analysts to ensure data quality and provide QA sign-off for production releases. Qualification Required: - 7+ years of experience in Data QA, ETL Testing, or BI/Data Engineering validation. - Strong hands-on experience in Microsoft Fabric, PySpark, and Spark SQL. - Experience supporting data migration projects and strong SQL skills for backend data validation. - Understanding of data quality principles such as Accuracy, Completeness, Consistency, and Timeliness. - Experience in designing or implementing QA automation in data platforms. - Exposure to CI/CD pipelines and DevOps integration for data testing. Additional Details: The company focuses on successful validation of Fabric migrations with zero critical data defects, implementing automated notebook-based data validation frameworks, reducing manual data testing efforts through automation, and ensuring high confidence in data accuracy across reporting and analytics layers. Note: Preferred qualifications, key technical skills, and success criteria have been omitted for brevity.