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Skill: Databricks QA Engineer / Senior Databricks QA Engineer Experience: 4-9 Years Locations: Pune | Bangalore | Hyderabad | Coimbatore Job Summary: We are looking for skilled Databricks QA Professionals with strong expertise in Data Testing, Databricks, SQL, PySpark, and Data Validation. The ideal candidate will be responsible for validating large-scale data processing pipelines, ensuring data quality across cloud-based data platforms, and testing end-to-end data engineering solutions built on Databricks. Key Responsibilities: - Perform testing of Databricks-based data pipelines and data transformation processes. - Validate data ingestion, transformation, aggregation, and loading workflows. - Develop and execute test plans, test cases, and test scenarios for data applications. - Perform source-to-target data validation and reconciliation. - Write and execute complex SQL queries for backend data validation. - Validate PySpark transformations and business rules. - Ensure data quality, completeness, consistency, and accuracy across multiple systems. - Perform functional, integration, regression, and data quality testing. - Analyze requirements, data models, and ETL/ELT workflows. - Identify, report, and track defects through closure. - Collaborate closely with Data Engineers, Architects, Product Owners, and Business Teams. - Participate in Agile ceremonies and quality assurance activities. Required Skills: - 4-9 years of experience in Data Testing / ETL Testing / QA. - Hands-on experience testing Databricks-based applications. - Solid expertise in SQL and database testing. - Experience with Data Warehouse and Data Lake concepts. - Good understanding of PySpark and Spark transformations. - Strong knowledge of data validation and reconciliation techniques. - Experience in source-to-target testing. - Familiarity with Agile/Scrum methodologies. - Experience with defect management tools such as Jira or Azure DevOps. Preferred Skills: - Experience with Azure Databricks. - Exposure to Delta Lake, Unity Catalog, and Lakehouse Architecture. - Experience with Azure Data Factory (ADF), Snowflake, Synapse, or AWS data services. - Knowledge of ETL/ELT testing methodologies. - Experience in test automation using Python or PySpark. - Insurance domain experience is an added advantage. Why Join ValueMomentum - Opportunity to work on cutting-edge cloud and data transformation programs. - Exposure to Databricks Lakehouse and modern data engineering technologies. - Continuous learning and certification opportunities. - Collaborative, inclusive, and innovation-driven culture. - Work with leading global insurance customers. Interested candidates can share their updated resume with the following details for - Total Experience: - Relevant Experience: - SQL Experience: - Current Location: - Preferred Location: - Current CTC: - Expected CTC: - Notice Period: .