Senior QA Data Engineer

We are seeking a Senior QA Data Engineer to join a dynamic team in London. In this hybrid role, you will design and implement robust test automation solutions for complex data pipelines and BI systems. You will play a critical role in ensuring the quality, reliability, and performance of data-driven applications throughout the software development lifecycle.

Our client is a leading global financial services institution with a strong presence in the banking sector. They are committed to leveraging cutting-edge technology to drive innovation and maintain excellence in their data-driven operations. The organization fosters a collaborative, high-performance culture that values technical expertise and continuous professional growth.

Responsibilities

• Plan, design, and execute comprehensive testing strategies for new features and system enhancements.
• Develop and maintain automated test cases to ensure thorough coverage across data pipelines.
• Champion test automation best practices to support continuous delivery and scalable solutions.
• Execute functional and non-functional test scenarios to validate system performance and reliability.
• Identify, analyze, and troubleshoot critical defects, performing root cause analysis in collaboration with development teams.
• Produce detailed defect reports to support efficient remediation and quality assurance.
• Communicate testing progress, risks, and quality insights to both technical and non-technical stakeholders.
• Mentor junior QA engineers and conduct code reviews to promote high standards of automation.

Requirements

• 6-8 years of experience in data quality assurance and test automation.
• Extensive experience validating data pipelines in Azure Data Factory and Azure Databricks.
• Advanced proficiency in Python (PyTest, PySpark, Pandas) or C# for building automated validation frameworks.
• Strong SQL skills for validating complex business rules and data transformations.
• Experience testing BI solutions including Power BI, SAP Business Objects, and Crystal Reports.
• Proven ability to integrate automated tests into CI/CD pipelines using Azure DevOps.
• Experience with traditional ETL tools such as Informatica and SSIS.
• Familiarity with modern data validation tools like Great Expectations and DataDiffPy.