Senior QA Engineer - Data Validation
First seen by Alion on Oct 21, 2026.
QA Senior Data Validation Engineer
Company : Blumetra Solutions
Experience : 6 - 8 Years
Job Function : Digital Assurance / Quality Engineering
Employment Type : Full-time
Job Summary :
Blumetra Solutions is looking for a skilled QA Senior Data Validation Engineer to perform data quality testing across enterprise data integration, ETL/ELT pipelines, cloud data platforms, and analytics solutions.
The role focuses on hands-on SQL validation, source-to-target reconciliation, API testing, integration testing, and test automation.
The ideal candidate will have practical experience with Python-based automation, Snowflake, cloud data environments, and AI-powered development tools such as Claude to improve testing efficiency and maintain reusable validation utilities.
Key Responsibilities :
- Data Validation and Testing : Execute data validation across ETL/ELT pipelines, data integration workflows, data models, Medallion Architecture (Bronze, Silver, and Gold layers), semantic models, dashboards, and reports.
- SQL and Reconciliation : Write and execute SQL queries to validate data accuracy, completeness, consistency, integrity, transformation rules, and source-to-target mappings.
- Database Testing : Perform database testing and investigate data discrepancies across source systems, staging layers, and target platforms.
- API Testing : Design and execute API tests to verify data exchange, service responses, integration behaviour, and error handling.
- End-to-End Testing : Conduct system integration and end-to-end testing across applications, data pipelines, and connected services.
- Test Automation : Develop, execute, and maintain automated test scripts using Python, Playwright, API automation tools, and suitable testing frameworks.
- AI-Assisted Automation : Use Claude or similar AI-powered tools to assist with test script development, automation improvements, test case preparation, defect analysis, and documentation.
- Cloud Data Testing : Perform validation and testing for Snowflake-based data solutions and cloud environments on AWS or Microsoft Azure.
- Data Lineage and Metadata : Validate data movement, transformation logic, metadata, lineage, and consistency across architectural layers.
- Defect Management : Identify, document, reproduce, and track defects; perform initial root-cause analysis and coordinate with developers and data engineers for resolution.
- Test Documentation : Prepare and maintain test cases, execution reports, defect logs, requirements traceability matrices (RTMs), and test summary reports.
- Quality Compliance : Follow established QA standards, test procedures, entry and exit criteria, and release validation processes.
- Agile Collaboration : Participate in sprint planning, daily stand-ups, backlog refinement, sprint reviews, and retrospectives using Jira.
- Continuous Improvement : Identify opportunities to improve test coverage, automation efficiency, validation accuracy, and reusable testing components.
Required Skills and Experience :
- 6 - 8 years of experience in QA, data testing, data validation, or quality engineering.
- Strong hands-on expertise in SQL, database testing, and data reconciliation.
- Practical experience with ETL/ELT testing, data integration testing, and source-to-target validation.
- Experience testing data models, reports, dashboards, and data transformations.
- Knowledge of API testing, system integration testing, and end-to-end testing.
- Hands-on experience with Python-based test automation, Playwright, or API automation tools.
- Experience using Claude or equivalent AI-powered tools for code assistance, test automation, or QA productivity.
- Experience with Snowflake and at least one cloud platform : AWS or Microsoft Azure.
- Understanding of data lineage, metadata, data modelling, and Medallion Architecture.
- Experience with defect tracking, test documentation, and Jira.
- Familiarity with Agile/Scrum delivery methodologies.
- Strong analytical, troubleshooting, communication, and collaboration skills.
Preferred Domain Experience :
- Retail and Supply Chain experience preferred.
- Life Sciences experience is an added advantage.
Ideal Candidate Profile :
- A technically strong QA engineer who can independently execute complex data validation, develop and maintain automated tests, investigate data quality issues, and collaborate with cross-functional teams to ensure reliable data delivery across enterprise platforms
Skills
Automation Testing, SQL, Python, ETL, Data Quality, ETL/Datawarehouse Testing, API Testing, Snowflake DB, Playwright Testing, Testing, Data Validation