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