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Africonology Solutions

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Data Quality Assurance & ETL Test Engineer

Discussion

Summary

Africonology Solutions is hiring a contract Data Quality Assurance & ETL Test Engineer in Johannesburg to ensure data pipelines, migrations, and Data & AI solutions are accurate, reliable, and reconciled. Day-to-day involves designing ETL/ELT test strategies, source-to-target validation, data profiling, reconciliation, and defect management using SQL, Python, cloud data platforms, and lakehouse en

Duties & Responsibilities

Data Quality Assurance & ETL Test Engineer

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

See also

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