We are looking for a highly skilled, experienced QA Engineer to play a foundational role in a newly formed Data-focused team. This position demands a quality-first mindset, strong test engineering capabilities, and proven experience validating data-intensive, cloud-native solutions. In this role, you’ll partner closely with Data Engineers, Data Stewards, and business stakeholders to ensure data products and pipelines are reliable, accurate, and fit for purpose while proactively identifying opportunities for continuous improvement. The ideal candidate brings strength in both manual and automated testing and thrives in a hands-on, collaborative, fast-paced agile environment. 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 About you 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