Collaborate with the engineering team to refine work requests in an agile development system
Develop comprehensive test plans and test cases as part of project planning
Provide accurate estimates of effort and duration of QA tasks
Create and maintain automated tests to validate pipeline requirements
Write and optimize SQL queries for automated validations
Build regression suites for critical datasets and dashboards
Create and maintain deterministic test datasets and “golden” expected results
Assist with the verification and recreation of user-reported data issues
File detailed and actionable defect reports
Work collaboratively with engineers to troubleshoot defects
Continuously improve QA processes, frameworks, and tools for data testing and validation
Integrate test automation with deployment and workflow tracking systems
Schedule and manage automated test runs, ensuring execution
Implement data observability checks and alerting
Collect, consolidate, and analyze test and monitoring results
Define and develop key performance indicators (KPIs) for measuring test effectiveness
Manage and prioritize work using the ticketing system
Conduct code reviews of test code and SQL validation logic
Partner with Data Engineering and BI stakeholders
Contribute to technical documentation of processes, tools, workflows, and standards
Mentor other team members by sharing knowledge, conducting training sessions, and providing guidance on best practices.

Bachelor’s degree in Computer Science, Information Systems /other relevant degree or equivalent professional experience
Demonstrated experience writing automated QA tests, especially for back-end systems without UI
Expert knowledge of relevant languages, such as SQL, Python, JavaScript, and/or C#
Expert knowledge of test automation tools such as Cypress, Great Expectations
Excellent analytical and problem-solving skills with a high level of attention to detail
Strong communication and collaboration skills to work effectively with cross-functional teams
Experience with CI/CD pipelines and version control systems (e.g., Jenkins, Git)
Knowledge of business intelligence tools such as Power BI or Tableau
Understanding of Agile development processes.

Senior Data QA Engineer

Key skills