Quality Engineering Lead/Senior– Data Validation &Automation Expert (AI Enabled)

Position1: QA Lead - Data Validation Expert (8 - 15 Yrs.)

Position 2: QA Senior - Data Validation Engineer (6 - 8 Yrs.)

Job Function: Digital Assurance / Quality Engineering
Employment Type: Full-time

Job Summary

Blumetra Solutions is looking for an experienced QA Lead – Data Validation to lead quality engineering initiatives across enterprise data integration, ETL/ELT pipelines, cloud data platforms, and analytics solutions.

The ideal candidate will have strong expertise in SQL, data validation, API testing, end-to-end system integration testing, and test automation. The role requires ownership of QA strategy, quality governance, customer coordination, and delivery stage gates. Experience leveraging AI-powered development tools such as Claude to build, deploy and maintain test automation utilities and QA accelerators is highly desirable.

Key Responsibilities

• QA Strategy & Leadership: Define and drive end-to-end QA strategies, test plans, test coverage, capacity planning/ estimations, and quality engineering standards for complex data projects.
• Data Validation: Lead validation with hands-on across data integrations, ETL/ELT pipelines, data models, Medallion Architecture (Bronze, Silver, and Gold layers), semantic models, dashboards, and visualizations.
• SQL & Data Reconciliation: Review and develop complex SQL queries to validate data accuracy, completeness, consistency, integrity, transformation logic, and source-to-target reconciliation.
• API & System Integration Testing: Drive API testing, end-to-end testing, and system integration testing across interconnected applications, services, and data platforms.
• Test Automation: Design and govern scalable automation frameworks using Python, Playwright, API automation tools, and other suitable technologies.
• AI-Assisted QA Engineering: Use Claude and other AI-powered tools to build and enhance validation utilities, automation accelerators, and reusable QA components. Leverage AI where appropriate for test preparation, RCA, summary reports and other documetation. Own automation utility/ scripts maintenance, version control, and deployment.
• Data Lineage & Metadata: Ensure appropriate validation of metadata, data lineage, transformation logic, and data movement across systems and architectural layers.
• Cloud & Data Platforms: Lead testing initiatives involving AWS or Microsoft Azure and Snowflake-based data solutions.
• Quality Governance & Stage Gates: Define and enforce QA entry and exit criteria, stage-gate checklists, release readiness assessments, defect closure requirements, and quality sign-offs.
• Defect Management: Drive defect triage, root-cause analysis, prioritization, resolution tracking, and risk communication.
• QA Documentation & Reporting: Review and maintain test strategies, test cases, requirements traceability matrices (RTMs), execution reports, defect reports, and test summary reports.
• Customer & Stakeholder Management: Work closely with customer teams, business stakeholders, developers, data engineers, and project managers to manage expectations, resolve issues, and ensure successful delivery.
• Team Leadership: Mentor QA engineers, review test deliverables, improve team productivity, and promote reusable frameworks and best practices.
• Agile Delivery: Participate in sprint planning, backlog refinement, daily stand-ups, sprint reviews, retrospectives, and release planning using Jira and related tools. Ensure Story/ task detailing with right level of acceptance criteria, calling out dependencies and risks upfront.

Required Skills & Experience

• 8–15 years of experience in QA, data testing, data validation, or quality engineering, including relevant leadership experience.
• Strong hands-on expertise in SQL and database testing.
• Proven experience in data integration testing, ETL/ELT validation, source-to-target reconciliation, reports testing.
• Strong understanding of data modelling, Medallion Architecture, semantic models, and visualization testing.
• Expertise in API testing, end-to-end testing, and system integration testing.
• Experience designing or governing automation frameworks using Python, Playwright, and API automation tools.
• Practical experience using Claude or equivalent AI-powered tools for code generation, automation development, and maintenance.
• Hands-on experience with Snowflake and at least one cloud platform: AWS or Microsoft Azure.
• Strong understanding of metadata, data lineage, and cross-system data flows.
• Experience owning QA governance, stage-gate reviews, test sign-offs, and release readiness.
• Strong customer-facing communication, stakeholder management, problem-solving, and team leadership skills.
• Experience working in Agile/Scrum environments and using Jira.

Preferred Domain Experience

• Retail and Supply Chain domain experience is preferred.
• Life Sciences domain experience is an added advantage.

Ideal Candidate Profile

A hands-on QA leader who understands business problem, has depth in domain/ functionality, combines technical depth in data validation and automation with the ability to own quality governance, lead team, engage customer, and ensure reliable data delivery across complex enterprise data ecosystems.