The Quality Engineer (QE) will play a key role in establishing a scalable, automation -driven QA framework across Data Intelligence initiatives. This role focuses on improving data quality, automation test efficiency, and release confidence for Azure -based platforms, including Databricks, Power BI, and Azure Functions. <\/div>
The QE will enable a shift -left testing approach, integrating QA early into the development lifecycle to ensure data integrity, system reliability, and continuous delivery alignment within a cloud -first environment. This is a hands -on engineering role for an experienced QE with deep data testing expertise, strong automation skills, and proven experience integrating QA into CI/CD pipelines. The resource will partner with Data Engineering, Analytics, and Development teams to deliver measurable improvements in quality, automation coverage, and defect prevention. <\/div>
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Key Deliverables <\/div>
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•Automated Test Framework Development: Design and implement reusable, scalable automation frameworks covering ETL pipelines, APIs, UI, and back -end data systems using Selenium and related tools. <\/div>
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•End -to -End Test Coverage: Provide comprehensive manual and automated test coverage across Dev, QA, and Production environments, ensuring validation of all data processing and reporting layers. <\/div><\/span>
Requirements<\/h3>
Soft Skills & Attributes <\/div>
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•Strong analytical, documentation, and communication skills. <\/div>
•Detail -oriented and highly organized with an automation -first mindset. <\/div>
•Proactive, self -driven, and capable of operating independently in a fast -paced environment. <\/div>
•Committed to continuous improvement and measurable quality outcomes. <\/div><\/span>