A global financial-services organization is seeking a senior QA Analyst to support a Cyber Data Operations team responsible for enterprise data platforms and analytical dashboards.
This highly technical QA position will ensure the accuracy, reliability, and completeness of data moving through complex warehouse and cloud-based environments. The successful candidate will use SQL and Python-based tools to validate data, automate testing, investigate defects, and verify ETL/ELT transformations from source through target.
This is not a traditional manual or UI-focused QA position. Candidates must be comfortable working directly with data and independently investigating why pipelines, transformations, or analytical outputs are incorrect.
RESPONSIBILITIES
Develop and execute detailed test plans, test cases, and test scripts
Test enterprise data pipelines, transformations, dashboards, and related data products
Validate ETL and ELT processing from source through target
Perform complex data validation and reconciliation using SQL
Use Python-based tools to automate testing, profiling, and quality checks
Test data-warehouse, data-lake, lakehouse, and cloud-platform functionality
Validate record counts, business rules, transformations, nulls, duplicates, and expected outputs
Investigate discrepancies and perform root-cause analysis
Identify, document, report, and track defects through resolution
Build and maintain reusable automation and regression-test coverage
Validate REST API behavior and resulting data
Maintain traceability between requirements, test cases, defects, and final validation
Perform functional, integration, regression, system, and user-acceptance testing
Partner with engineers, developers, and stakeholders in an Agile/Scrum environment
Role Requirements:
At least eight years of experience in QA, data testing, ETL/ELT testing, data engineering, or a related discipline