Lead QA Automation Engineer

Overview

We are modernizing a legacy application by transitioning it to modern technologies and migrating it to the cloud. This is a high-impact initiative requiring strong QA leadership to ensure a smooth, reliable transformation.

Responsibilities

• Collaborate with cross-functional teams and clients to define optimal quality strategies and communicate QA plans to technical and business stakeholders.
• Adapt quickly to customer environments and delivery models.
• Promote and advocate QA approaches, tools, and methodologies within the organization.
• Provide accurate estimations and effectively decompose testing tasks.
• Prioritize testing based on business impact and technical risk.
• Lead and mentor a distributed QA team across multiple time zones.
• Define and implement end-to-end testing strategies, including during pre-sales and solutioning phases.
• Evaluate and recommend testing tools and automation frameworks.
• Communicate test results, quality metrics, and improvement plans to management and clients.
• Maintain comprehensive and up-to-date QA documentation.
• Design and maintain test cases and automated test scripts.
• Manage defect lifecycle and reporting using standard tracking systems.
• Continuously improve QA processes, tools, and coverage.

Skills

Must have

• 5+ years in QA Automation and 2+ years in a Lead role.
• Proven experience building automation frameworks from scratch.
• Strong proficiency in Java, Python, or Golang.
• Solid understanding of QA methodologies and SDLC.
• Experience leading distributed teams.
• Expertise in both manual and automated testing.
• Hands-on with API testing (SOAP/REST).
• Familiarity with legacy systems and modernization challenges.
• Experience with unit testing frameworks.
• Excellent communication and stakeholder management skills.
• Passion for continuous learning and improvement.

Nice to have

• Exposure to AI-powered testing and defect analytics tools.
• Experience defining QA strategies for modernization or transformation projects.
• Understanding of predictive quality metrics and risk-based testing.