Overview

Senior QA Engineer: 6–8 Years - 2 positions

Responsibilities

• Data Validation & Testing: Validate data integrations, ETL/ELT pipelines, data models, Medallion Architecture (Bronze, Silver, and Gold layers), semantic models, dashboards, and visualizations.
• SQL Testing: Write and execute SQL queries to verify data accuracy, completeness, consistency, integrity, transformation logic, and source-to-target reconciliation.
• API & Integration Testing: Perform API testing, end-to-end testing, and system integration testing across applications, services, and data platforms.
• Test Automation: Develop and maintain automated test scripts, frameworks, and reusable validation utilities using Python, Playwright, API automation tools, and other relevant technologies.
• Data Lineage & Metadata Validation: Validate data lineage, metadata, transformation rules, and data movement across different systems and architectural layers.
• AI-Assisted Test Development: Use Claude or other AI-powered tools to develop, enhance, and maintain data validation utilities, automation scripts, and QA accelerators. Support automation utility/ scripts maintenance, version control, and deployment.
• Cloud & Data Platform Testing: Test data pipelines and integrations involving AWS or Microsoft Azure and Snowflake/ Databricks.
• Functional Testing: Understand business requirements and functional workflows to design relevant test scenarios and validate expected business outcomes.
• Test Documentation: Prepare and maintain test plans, test cases, requirements traceability matrices (RTMs), test execution reports, defect reports, and test summary reports. Leverage AI for documentation as much as possible.
• Defect Management: Identify, document, track, and retest defects. Participate in defect triage and root-cause analysis with development and data engineering teams.
• Quality Checklists: Execute QA entry and exit checklists, support stage-gate reviews, and ensure testing deliverables meet defined acceptance criteria.
• Stakeholder Collaboration: Coordinate with developers, data engineers, business analysts, project managers, and customer teams to resolve issues and ensure quality deliverables with an intent of ownership to close the open items.
• Agile Delivery: Participate in sprint planning, daily stand-ups, sprint reviews, retrospectives, and other Agile/Scrum activities using Jira. Ensure Story/ task detailing with right level of acceptance criteria, calling out dependencies and risks upfront.

Qualifications

• 3–8 years of relevant experience in QA, data testing, data validation, or quality engineering, depending on the position.
• Strong SQL skills and experience validating data across source and target systems.
• Hands-on experience with ETL/ELT testing, data integration, data reconciliation, and data quality assurance.
• Understanding of data modelling, Medallion Architecture, semantic models, and visualization testing.
• Experience in functional, API testing and end-to-end system integration testing.
• Hands-on experience with Python-based automation, Playwright, API automation, or comparable testing frameworks.
• Understanding of metadata, data lineage, transformation logic, and cross-system data flows.
• Experience using Claude or equivalent AI tools for automation development and code assistance.
• Working experience with Snowflake/ Databricks and at least one cloud platform: AWS or Microsoft Azure.
• Strong analytical, troubleshooting, documentation, and communication skills.
• Familiarity with Jira and Agile/Scrum methodologies.
• Execute data validation, SQL testing, functional, API testing, and integration testing activities.
• Develop and maintain automation scripts and reusable test utilities.
• Prepare test cases, traceability documentation, execution reports, and defect records.
• Investigate data discrepancies and collaborate with engineering teams to resolve issues.
• Follow established test strategies, quality checklists, and reporting standards.
• Own end-to-end testing activities for complex data integrations and pipelines.
• Design comprehensive test scenarios, validation strategies, and reusable automation components.
• Independently manage test execution, defect triage, quality reporting, and testing risks.
• Review test cases and automation scripts and mentor junior QA engineers where required.
• Coordinate with customer and cross-functional teams to resolve complex quality issues.
• Support QA stage gates, release readiness assessments, and continuous improvement initiatives.
• Retail and Supply Chain domain experience is preferred.
• Life Sciences domain experience is an added advantage.