QA Lead – Data Engineering & ETL

About the Role:

We are looking for an experienced QA Lead with a strong background in Data Engineering and ETL testing to lead quality assurance activities for enterprise data platforms. The ideal candidate should have expertise in both manual and automation testing, possess excellent SQL skills for complex data validation, and have prior experience leading QA teams.
The role requires regular collaboration with onshore stakeholders, mentoring offshore team members, driving quality initiatives, and proactively managing risks throughout the project lifecycle.

Requirements

Required Skills:

• 8–10 years of overall IT experience.
• Minimum 5+ years of experience in Data Engineering / ETL Testing.
• Strong experience in Manual and Automation Testing.
• Excellent SQL skills with experience writing complex queries, joins, aggregations, stored procedures, and data validation scripts.
• Experience validating large datasets and complex ETL/data transformation workflows.
• Hands-on experience working with enterprise data platforms and technologies such as:
  • Apache Airflow
  • Databricks
  • Profisee (Master Data Management)
• Strong understanding of QA methodologies, defect lifecycle, and testing best practices.
• Excellent communication, analytical, and stakeholder management skills.
• Understand the business requirements and frame test strategy and test cases
• Reporting status of test execution to required stakeholders in a timely manner.

Preferred Skills

• Experience with Python for automation or data validation.
• Exposure to Azure services and cloud-based data platforms.
• Experience working in Agile/Scrum environments.
• Familiarity with CI/CD pipelines and DevOps practices.
• Lead and mentor QA engineers to ensure high-quality deliverables.
• Work closely with onshore counterparts and business stakeholders.
• Drive ownership, accountability, and quality across the team.
• Provide regular feedback to team members and support their professional growth.
• Communicate risks, dependencies, and project status effectively to all stakeholders.

Responsibilities

Key Responsibilities:

• Lead the QA team and own end-to-end testing activities for data engineering solutions.
• Define, review, and execute test strategies, test plans, and test cases.
• Perform both Manual and Automation Testing across multiple releases.
• Validate ETL pipelines, data transformations, and business rules.
• Write and execute complex SQL queries for data validation, reconciliation, and root cause analysis.
• Collaborate closely with development teams to ensure quality throughout the SDLC.
• Coordinate regularly with onshore stakeholders and provide clear status updates.
• Mentor team members, review deliverables, and drive continuous improvement.
• Proactively identify risks, raise concerns early, and ensure timely resolution.
• Participate in defect triage, release validation, and production support activities when required.

Benefits

Insurance 
Career Development 
Flexible Work hours 
Learning Opportunities
Inclusive and collaborative work culture