Test Data QA Engineer

We are looking for an experienced Test Data QA Engineer with strong expertise in Test Data Management, QA methodologies, Neo4j, and exposure to AI-assisted development/testing tools such as Windsurf. The candidate will be responsible for creating, validating, and managing test data across applications and ensuring data accuracy, integrity, and completeness throughout the testing lifecycle., * Design, create, and maintain test data for functional, integration, regression, and end-to-end testing.

• Develop test scenarios and test cases focusing on data validation and data quality.
• Perform backend/database testing using SQL and Neo4j.
• Validate nodes, relationships, properties, and data integrity within Neo4j graph databases.
• Develop and execute Cypher queries for test data validation and verification.
• Validate data movement and transformation across source and target systems.
• Perform data reconciliation and identify discrepancies between upstream and downstream systems.
• Work closely with developers, data engineers, business analysts, and QA teams to understand test data requirements.
• Support creation and maintenance of reusable test data sets for different testing environments.
• Perform data validation for ETL/data pipelines and application integrations.
• Develop and maintain automated test scripts for data-driven testing.
• Leverage AI-assisted tools and Windsurf to improve QA productivity, test development, code analysis, and automation activities.
• Identify defects, document findings, and work with development teams through defect resolution and retesting.
• Perform root-cause analysis for data-related defects and testing failures.
• Support regression testing and production validation activities.
• Ensure test data follows applicable data privacy, security, and masking requirements.
• Participate in Agile ceremonies, test planning, estimation, and release activities.
• Maintain test documentation, test results, defect reports, and traceability.

The ideal candidate should have hands-on experience working with complex data environments, graph databases, database validation, test automation, and AI-assisted testing practices., * 5+ years of experience in QA, Data Testing, or Test Data Management.

• Strong knowledge of Test Data Management (TDM) concepts and practices.
• Hands-on experience with database and backend testing.
• Strong experience with Neo4j or graph database testing.
• Knowledge of Cypher Query Language.
• Strong SQL and data validation skills.
• Experience validating large and complex datasets.
• Experience in ETL/data pipeline testing and source-to-target validation.
• Good understanding of data quality, data reconciliation, and data integrity.
• Experience in functional, integration, regression, and end-to-end testing.
• Experience with test automation frameworks.
• Knowledge or hands-on exposure to AI-assisted testing/development.
• Knowledge of Windsurf or similar AI-assisted development tools.
• Strong analytical, troubleshooting, and problem-solving skills.

Preferred Skills

• Python knowledge for test automation and data validation.
• Experience with API testing and automation.
• Exposure to cloud-based data platforms such as AWS or Azure.
• Understanding of CI/CD and automated testing pipelines.
• Experience testing graph-based or highly interconnected datasets.
• Familiarity with GenAI/AI-based test case generation and QA productivity tools.
• Experience working in Agile/Scrum environments.

Key Competencies

• Test Data Management
• Data QA & Validation
• Neo4j
• Cypher
• AI-Assisted Testing
• Windsurf
• SQL
• Test Automation
• ETL / Data Pipeline Testing
• Data Reconciliation
• Data Quality
• Defect Management
• Root-Cause Analysis