Test Data QA Engineer

Job Description: Test Data QA Engineer

Role: Test Data QA Engineer

Location: Copell, TX/ NYC, NY /St Louis, MO in Hybrid Mode or open to remote if someone is not local to the location)

Duration: Long term

C2C or W2

Experience: 5+ Years

Key Skills: Test Data Management, QA, Neo4j, AI, Windsurf, SQL, Automation Testing

Job Summary

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.

The ideal candidate should have hands-on experience working with complex data environments, graph databases, database validation, test automation, and AI-assisted testing practices.

Key Responsibilities

• 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.

Required Skills

• 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