Data QA Engineer

Key Responsibilities

• Develop, maintain, and execute comprehensive test strategies, test plans, and test cases for data pipelines, datasets, and related data products.
• Proactively identify quality risks, testing gaps, and areas for improved QA coverage
• Identify, document, and track defects in Azure DevOps
• Partner closely with Data Engineers to drive timely defect fixes and verify remediation.
• Collaborate with cross-functional stakeholders to strengthen quality processes, documentation, and overall release readiness.
• Provide input into long-term QA strategy and continuous improvement initiatives.
• Perform other duties as assigned

Skills, Knowledge & Expertise

• Degree in Computer Science, Software Engineering, Information Systems, or a related field is preferable.
• Proven QA/testing experience with data-intensive applications, ideally within cloud-native environments.
• Strong command of testing methodologies (functional, regression, integration, performance) and defect lifecycle management.
• Hands-on experience with test automation (e.g., Python or similar) and writing SQL queries for data validation and reconciliation.
• Experience testing data warehouses/lakes and pipelines; familiarity with data quality concepts and tooling is a plus.
• Exposure to Microsoft Azure services and modern data platforms (e.g., Synapse, Snowflake).
• Strong SQL skills for data validation, reconciliation, and troubleshooting.
• Understanding of loan lifecycle data (servicing, arrears, recoveries, asset resolution) or the ability to ramp up quickly.
• Resourceful, motivated self-starter with the ability to collaborate across business and technology teams