Lead Quality Engineer - R01557793

Team: AI & Data Engineering : Data Engineering

Location: Bangalore, Karnataka, India

Commitment: Employee

Workplace Type: hybrid

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.