Quality Engineering Lead - Data Validation & Automation

Lead Quality Engineering

Blumetra Solutions is seeking an experienced QA Lead - Data Validation Expert to lead quality engineering initiatives across enterprise data integration, ETL/ELT pipelines, cloud data platforms, and analytics solutions. The role combines hands-on data validation and test automation with QA strategy, governance, team leadership, and customer engagement.

Key Responsibilities :

- Define QA strategies, test plans, test coverage, effort estimation, resource planning, and quality engineering standards for complex data projects.

- Lead validation across data integration pipelines, ETL/ELT processes, data models, Medallion Architecture, semantic models, dashboards, and reports.

- Review and develop complex SQL queries to validate data accuracy, completeness, consistency, integrity, transformation logic, and source-to-target reconciliation.

- Lead API testing, end-to-end testing, and system integration testing across interconnected applications and data platforms.

- Design and govern scalable automation frameworks using Python, Playwright, API automation tools, and other suitable technologies.

- Leverage Claude and similar AI-powered tools to develop automation accelerators, validation utilities, reusable QA components, and documentation.

- Lead quality initiatives involving Snowflake and cloud platforms such as AWS or Microsoft Azure.

- Ensure validation of metadata, data lineage, transformation logic, and cross-system data movement.

- Establish QA entry and exit criteria, stage-gate reviews, release readiness assessments, defect closure requirements, and quality sign-offs.

- Lead defect triage, root-cause analysis, prioritization, resolution tracking, and quality risk communication.

- Coordinate with customers, business stakeholders, developers, data engineers, and project managers to ensure successful delivery.

- Mentor QA engineers, review deliverables, improve productivity, and establish reusable testing standards.

- Participate in sprint planning, backlog refinement, daily stand-ups, sprint reviews, retrospectives, and release planning using Jira.

Required Skills :

- 8 - 12 years of experience in QA, data testing, data validation, or quality engineering, including leadership responsibilities.

- Strong hands-on expertise in SQL, database testing, ETL/ELT validation, and source-to-target reconciliation.

- Experience testing data models, semantic models, dashboards, reports, and data visualizations.

- 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 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, data flows, and Medallion Architecture.

- Proven experience in QA governance, release readiness, quality sign-offs, and stakeholder management.

- Experience working in Agile/Scrum environments and using Jira.

- Strong communication, analytical, problem-solving, and team leadership skills.

Preferred Domain Experience :

- Retail and Supply Chain experience preferred.

- Life Sciences experience is an added advantage.

Skills

Automation Testing, Data Validation, SQL, Python, ETL, API Testing, Snowflake DB, Playwright Testing, Testing, ETL/Datawarehouse Testing, Data Quality