Database Tester

Job Title: Database Tester Location: Bangalore, Pune, Chennai Experience: 5-10 Years Job Description We are looking for a skilled Data QA Engineer / Data Test Engineer with 5+ years of experience in data quality assurance, data validation, and testing enterprise data platforms. The ideal candidate should possess a strong foundation in Data Engineering, with hands-on expertise in Python, PySpark, SQL/T-SQL, Data Reconciliation, and Power BI validation. Experience working with Microsoft Fabric, Databricks, Lakehouse, and Medallion Architecture is highly preferred. The role involves validating migrated datasets, developing automated test frameworks, performing data reconciliation between legacy and modern data platforms, and ensuring the accuracy, consistency, and integrity of enterprise reporting solutions. Roles Responsibilities Design, develop, and execute end-to-end data validation and reconciliation strategies between legacy data platforms and Microsoft Fabric/Databricks environments. Perform apple-to-apple data reconciliation by comparing source and target datasets to ensure data accuracy, completeness, and consistency. Validate Cascade 2.0 business rules, column mappings, channel mappings, and transformation logic against source systems. Develop automated data quality, regression, and reconciliation frameworks using Python and PySpark. Write and optimize advanced SQL/T-SQL queries for data validation, reconciliation, and defect analysis across multiple environments. Validate Power BI reports, dashboards, datasets, filters, calculations, and Row-Level Security (RLS) to ensure accurate business reporting. Define and execute data quality checks, including row count validation, duplicate detection, null value validation, referential integrity, and business rule verification. Establish pass/fail criteria for data validation based on row counts, KPIs, key measures, and reconciliation thresholds. Identify, document, track, and resolve data quality issues and defects using defect management tools. Collaborate with Data Engineers, BI Developers, QA teams, and business stakeholders to resolve data discrepancies before production deployment. Perform regression, integration, system, and user acceptance testing (UAT) for enterprise data pipelines and reporting solutions. Participate in Agile ceremonies including sprint planning, daily stand-ups, sprint reviews, retrospectives, and defect triage meetings. Create and maintain comprehensive test plans, test cases, validation reports, reconciliation documents, and testing evidence. Disclaimer : This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying. Job Title: Database Tester Location: Bangalore, Pune, Chennai Experience: 5-10 Years Job Description We are looking for a skilled Data QA Engineer / Data Test Engineer with 5+ years of experience in data quality assurance, data validation, and testing enterprise data platforms. The ideal candidate should possess a strong foundation in Data Engineering, with hands-on expertise in Python, PySpark, SQL/T-SQL, Data Reconciliation, and Power BI validation. Experience working with Microsoft Fabric, Databricks, Lakehouse, and Medallion Architecture is highly preferred. The role involves validating migrated datasets, developing automated test frameworks, performing data reconciliation between legacy and modern data platforms, and ensuring the accuracy, consistency, and integrity of enterprise reporting solutions. Roles Responsibilities Design, develop, and execute end-to-end data validation and reconciliation strategies between legacy data platforms and Microsoft Fabric/Databricks environments. Perform apple-to-apple data reconciliation by comparing source and target datasets to ensure data accuracy, completeness, and consistency. Validate Cascade 2.0 business rules, column mappings, channel mappings, and transformation logic against source systems. Develop automated data quality, regression, and reconciliation frameworks using Python and PySpark. Write and optimize advanced SQL/T-SQL queries for data validation, reconciliation, and defect analysis across multiple environments. Validate Power BI reports, dashboards, datasets, filters, calculations, and Row-Level Security (RLS) to ensure accurate business reporting. Define and execute data quality checks, including row count validation, duplicate detection, null value validation, referential integrity, and business rule verification. Establish pass/fail criteria for data validation based on row counts, KPIs, key measures, and reconciliation thresholds. Identify, document, track, and resolve data quality issues and defects using defect management tools. Collaborate with Data Engineers, BI Developers, QA teams, and business stakeholders to resolve data discrepancies before production deployment. Perform re