Senior Quality Assurance Engineering Lead
New
G
GoGuardianEducation Technology
Location: IndiaFull-TimeLead
Salary not disclosed
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Job Details
- Required Skills
- CypressAPI testingSeleniumCI/CDQuality AssurancePlaywright
Requirements
- Strong experience in software quality assurance, including hands-on functional, integration, regression, exploratory, and release testing.
- Experience leading QA activities for a product, project, or engineering team.
- Solid understanding of test strategy, risk-based testing, impact analysis, and defect management.
- Practical experience with web and API automation using tools such as Playwright, Cypress, or Selenium.
- Understanding of automation frameworks, CI/CD pipelines, test execution, and maintenance of automated tests.
- Comfortable working with stakeholders to resolve requirement, quality, and delivery concerns.
- Ability to break down complex features into test areas and provide realistic estimates.
- Clear communication skills regarding risks, blockers, and progress.
- Experience mentoring team members in testing, debugging, and automation.
- Willingness to learn new product areas and support cross-functional teams.
- Bachelor’s degree in Computer Science, Engineering, or related field, or equivalent practical experience.
Responsibilities
- Own the overall QA strategy, test planning, test execution, and release-readiness assessment for an assigned product area.
- Work closely with Product Managers, Developers, and Technical Leads to review requirements, identify gaps, and define appropriate test coverage.
- Create risk-based test strategies for large features and technical initiatives.
- Lead and support manual, API, integration, and automation testing across web-based applications and services.
- Contribute to the design, implementation, maintenance, and improvement of test automation frameworks.
- Monitor CI/CD automation results, investigate failures, and address product or test environment issues.
- Mentor QA team members through test-case reviews, requirement analysis, and technical feedback.
- Track QA progress, risks, and dependencies, and communicate them to leadership.
- Identify opportunities to improve QA processes and drive adoption of AI-assisted QA workflows.
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