Lead Quality Engineer
Primary Skills
- ETL Testing, SQL, Databricks testing.
Specialization
- ETL Specialization: Senior Lead Data Engineer
Job requirements
- Data Intelligence QA Role:
- We’re seeking an experienced and technically strong Quality Engineer (QE) to help transform our QA function. This is a hands-on role for professionals with a strong mix of data domain expertise, test automation experience, and CI/CD pipeline knowledge.
- The QE will be instrumental in building scalable, automated test frameworks that support our cloud-first architecture on Azure, with heavy use of Databricks, Power BI, and Azure Functions.
- The ideal candidate is comfortable working in a fast-paced, Agile environment and has experience across both data and software testing—with an eye toward continuous improvement and quality at scale.
Key Responsibilities Automation & QA Engineering
• Design, develop, and maintain automated test frameworks.
• Build reusable automated test suites for ETL pipelines, APIs, UI, and back-end systems. • Integrate tests into CI/CD pipelines using GitHub Actions.
• Lead the effort to shift from manual QA to automation across platforms.
Test Planning & Execution
• Create and manage test plans and cases using Jira, Confluence and SharePoint.
• Execute both manual and automated tests across Dev, QA, and Prod environments.
• Track, manage, and validate defects using Jira. Data Platform & Reporting Validation.
• Perform deep data validations on Databricks, Power BI, and Azure-based data flows.
• Collaborate with Data Engineers, Analysts, and BAs to ensure data integrity and test coverage.
• Implement automated ETL validation to catch data quality issues early in the cycle. CI/CD Pipeline Integration
• Set up and optimize CI/CD pipelines, ensuring test automation is fully integrated.
• Participate in post-deployment validations and production readiness checks.
• Support disaster recovery testing and environment stability checks. AI • Build and maintain AI-assisted automated test cases
• Leverage AI capabilities for intelligent test case creation and optimization within Jira.
Required Skills & Experience
• Strong QA engineering skills and experience, including test automation and CI/CD. • Strong knowledge of GitHub, GitHub Actions, and CI/CD practices.
• Experience with SQL for data validation and automated testing in data platforms.
• Proven experience testing in Azure environments (e.g., Databricks, Azure Functions, Power BI).
• Familiarity with Agile methodologies and sprint-based development cycles.
• Hands-on experience with AI, Jira, Confluence, Git, and SharePoint. Preferred Qualifications
• Experience setting up CI/CD pipelines from scratch or optimizing existing workflows.
• Background in data security and compliance (e.g., PHI, data masking, access control).
• Experience with performance/load testing tools.
• Knowledge of testing in AI/ML or data science workflows is a strong plus. Soft Skills
• Strong communication and collaboration skills across technical and business teams.
• Detail-oriented, with a mindset for continuous improvement and automation-first thinking.
• Self-starter with the ability to manage time and tasks independently.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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