SQA Engineer

Department: Quality Assurance
Reports To: QA Lead / Project Manager

Role Overview

We are looking for a Mid-Level QA Engineer who takes full ownership of quality across assigned features or modules. This role goes beyond executionfocusing on test design risk identification cross-system validation and active contribution to automation. You will work closely with Product Managers and Developers to ensure issues are prevented early and quality is built into the development lifecycle.

Automation is a core expectation at this level. The ideal candidate can translate manual regression into stable automated tests and actively improve overall testing efficiency.

Key Responsibilities

Quality Ownership & Testing

• Own end-to-end testing for assigned features or modules
  
• Design and execute test plans and test strategies based on requirements and risks
  
• Perform advanced functional regression integration and system testing
• Identify quality risks early and communicate them clearly to stakeholders
  
• Ensure acceptance criteria and business requirements are fully validated
  
  

API Integration & Advanced Testing

• Perform advanced API testing for critical workflows
  
• Validate cross-system integrations and data consistency
• Catch integration defects early in the development cycle
  
• Analyze logs responses and backend behavior to identify root causes
  
  

Performance & Security Testing

• Execute and analyze basic performance testing (e.g. JMeter k6)
  
• Conduct security testing using OWASP Top 10 guidelines
  
• Report performance bottlenecks and security risks with clear evidence
  
  

Automation & Efficiency

• Write and maintain basic automated test scripts
• Convert high-value manual regression cases into automation
  
• Debug and stabilize failing automated tests
  
• Integrate automation into regression cycles and CI pipelines (with guidance)
  
• Collaborate with developers to improve test reliability and stability
  
  

Collaboration & Mentorship

• Collaborate closely with Product Managers and Developers on requirements and testability
  
• Participate actively in sprint ceremonies and quality discussions
  
• Mentor Junior QA Engineers and review their test cases
  
• Promote best practices in testing and documentation
  

Required Skills & Qualifications

Core QA Skills

• Strong understanding of test planning and test strategy
• Experience with white-box testing logic validation and edge cases
  
• Solid knowledge of SDLC & STLC
• Strong debugging analytical and problem-solving skills

  
  

Technical Skills

• Advanced API testing (Postman or equivalent)
  
• Experience with integration testing and data validation
• Basic experience with performance testing tools (JMeter k6)
  
• Understanding of OWASP Top 10 security concepts
• Familiarity with automation frameworks and scripting (any stack)
  
  

Tools

• Bug tracking & test management tools (Jira ClickUp etc.)
  
• Automation tools/frameworks (e.g. Cypress Playwright Selenium or similar)
  
• CI/CD awareness is a plus
  

Automation Expectations (Execution Level)

At the Mid-Level automation is an active responsibility not optional.

You are expected to:

• Write and maintain automated regression tests
  
• Identify automation-worthy scenarios
  
• Reduce manual regression execution time
  
• Maintain stable and reliable automated tests
  
• Contribute consistently to the automation suite
  

Goal: Actively build maintain and improve automation coverage.

Success Metrics (KPIs)

1. Quality Ownership

• Defect leakage rate to production
  
• Regression effectiveness (issues caught pre-release)
  
• Acceptance rate of QA sign-offs
  
• Reduction in post-release issues
  

2. Test Strategy & Coverage

• Completeness and accuracy of test plans
  
• Coverage across functional integration performance and security testing
  
• Early identification of high-risk areas
  

3. API & Integration Testing

• Number of integration defects caught pre-release
  
• API coverage for critical workflows
  
• Cross-system data validation accuracy
  

4. Automation Contribution

• % of regression suite automated
  
• Number of automation scripts created or maintained
  
• Reduction in manual regression effort
  
• Automation stability (pass rate flakiness)