QA Engineer / Senior QA Engineer – Data Validation & Automation (AI Enabled)

QA Engineer (Mid-Level): 3–5 Years - 2 positions

Senior QA Engineer: 6–8 Years - 2 positions

Job Function: Digital Assurance / Quality Engineering

Employment Type: Full-time

Job Summary Blumetra Solutions is seeking Application and Data Validation Engineers with strong expertise in data validation, SQL, ETL/ELT testing, API testing, functional testing and end-to-end system integration testing.

The successful candidates will be responsible for validating data pipelines, integrations, data models, analytics solutions & Applications while developing automated test scripts and reusable validation utilities. Experience with Python, Playwright, Snowflake/ Databricks, AWS or Azure, and AI-assisted development tools such as Claude is highly desirable.

Candidates should demonstrate strong ownership, analytical skills, attention to detail, and the ability to translate business requirements into comprehensive test scenarios and data quality checks.

Key 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.

Required Skills & Experience

• 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 comm…