Senior QA Engineer (Data Products)

SUMMARY:
Our client in the Connectivity & Networking sector is seeking a Senior QA Engineer (Data Products) on a contract duration of 6 months.

Role Purpose

POSITION INFO:
Key Responsibilities Design and execute functional testing strategies for data products, APIs, dashboards and analytics applications. Validate data accuracy, completeness and consistency across data pipelines, datasets and reporting layers. Perform end-to-end testing of data flows from ingestion through transformation to visualisation and insight delivery. Conduct performance, load and stress testing of data platforms, APIs and reporting systems. Develop automated test scripts for data validation, regression testing and pipeline quality assurance. Identify, document and track defects in data, logic, transformations and system behaviour. Collaborate with Data Engineers, API Developers, Platform Engineers and Solution Architects to resolve quality issues. Validate data models, business logic, calculations and analytical outputs against business requirements. Ensure data quality checks are embedded across ETL\/ELT pipelines and data transformation processes. Support testing of ML outputs, scores, ADR datasets and analytics features where applicable. Contribute to test strategy, QA standards and best practices for data products and analytics systems. Participate in Agile ceremonies and provide QA input during sprint planning, reviews and release cycles. Qualifications & Experience Bachelor's degree in Computer Science, Information Systems, Software Engineering, Data Science or a related field. 5-8 years' experience in QA engineering, data testing or software testing roles. Strong experience in data validation, ETL testing and analytics testing. Experience testing APIs, data pipelines and BI\/visualisation tools. Knowledge of SQL and ability to validate complex datasets and transformations. Experience with automation testing tools and frameworks is advantageous. Familiarity with performance and load testing tools (e.g. JMeter, Gatling or similar). Experience working in cloud data environments (Azure, AWS or Google Cloud Platform) is advantageous. Experience in telecommunications, analytics or large-scale data environments is preferred. Key Competencies Data quality assurance and validation ETL\/ELT testing and pipeline verification API and integration testing Performance and load testing SQL and data analysis Test automation and scripting Defect management and root cause analysis Analytical thinking and attention to detail Agile QA practices Collaboration across engineering teams

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