Data quality assurance & etl test engineer
Summary
Designs and executes ETL/ELT and data-quality testing for banking data pipelines, migrations, and Data & AI solutions at a client site in Johannesburg. Day to day: source-to-target validation, reconciliation, data profiling, defect management, and test automation using SQL, Python, and cloud data platforms.
Location: Gauteng, Johannesburg
Job Type: Contract, Full-Time Job Description
Our client is seeking a Data Quality Assurance and ETL Test Engineer that will be responsible for ensuring that data pipelines, data products, migrations, and Data & AI solutions are accurate, complete, reliable, reconciled and fit for business use from a testing perspective.
ETL / ELT Testing: Design and execute ETL/ELT test strategies, scenarios and test cases. Perform source-to-target validation. Validate data transformations, mappings, joins, calculations and business rules. Test full and incremental data loads. Validate exception and error handling. Perform regression testing following pipeline or schema changes. Validate data across source, ingestion, transformation and consumption layers. Identify and document data defects and support root-cause analysis.
Data Quality Assurance: Develop and execute data-quality validation rules. Validate data for accuracy, completeness, consistency, validity, uniqueness and timeliness. Perform data profiling and identify anomalies. Develop data-quality checks and controls. Perform data reconciliation and investigate discrepancies. Support the establishment of repeatable data-quality testing practices.
Testing Documentation & Defect Management: Test strategies and plans. Test scenarios and test cases. Test data requirements. Test execution evidence. Defect logs. Defect root-cause analysis. Test completion and release-readiness reports. Data reconciliation results.
Experience required: ETL/ELT testing Data quality assurance Advanced SQL Data reconciliation Data migration testing Test automation Python or equivalent scripting Data pipeline testing API/integration testing Cloud data platforms Data Lake/Lakehouse environments Data & AI use-case testing
Significant Advantage: Experience in Transactional Banking is mandatory. Experience in Payments, Trade, Cash/Liquidity Management, Investor Services, transaction processing, or other high-volume financial-services environments would be particularly relevant. Understand the importance of data accuracy, reconciliation, financial controls, and the business impact of data defects in a transactional environment. Desired Experience & Qualification
Data, Quality, Assurance, ETL, Test, Engineer #J-18808-Ljbffr