G18 - Software Quality Engineer

About the Role

We are looking for an experienced Quality Assurance (QA) Engineer / Quality Engineer to join our team. You will play a key role in ensuring the quality, reliability, and performance of complex distributed systems through automated testing, regression testing, and robust quality engineering practices.

Key Responsibilities

• Collaborate with cross-functional Agile teams, including Software Engineers, Product Managers, and Designers, to understand requirements, define acceptance criteria, and ensure end-to-end quality.
• Develop, maintain, and execute automated regression test suites using JavaScript/TypeScript and Playwright.
• Perform end-to-end testing across React.js frontend and NestJS backend applications.
• Integrate automated tests into CI/CD pipelines such as GitHub Actions and GitLab CI to enable continuous testing and rapid feedback.
• Manage test environments, container-based testing setups, database states, data dumps, and mock data for test execution and environment resets.
• Conduct database and data validation testing across SQL and NoSQL databases, including PostgreSQL, MySQL, and MongoDB.
• Collaborate with stakeholders and government agencies to deliver reliable, secure, and high-quality software systems.
• Participate actively in Scrum ceremonies, technical sharing, and quality engineering discussions.

Requirements

• Experience testing large-scale, high-availability software systems.
• Strong proficiency in JavaScript / TypeScript for test automation.
• Hands-on experience with Playwright for web and API end-to-end automation.
• Experience testing applications built with React.js and NestJS.
• Experience developing and maintaining automated regression test suites.
• Experience integrating automated testing into CI/CD pipelines.
• Good knowledge of database testing, including database dumps, mock data, data validation, and environment setup.
• Experience with PostgreSQL, MySQL, MongoDB, or similar databases.
• Hands-on experience with Docker, Kubernetes, or other container technologies.
• Experience with cloud platforms such as AWS (preferred), Azure, or GCP.
• Familiarity with observability, monitoring, and log analysis tools such as ELK/Kibana, AWS CloudWatch, or Splunk.

Good to Have

• Experience designing and executing performance testing, including load, stress, spike, and endurance/soak testing.
• Hands-on experience with k6, Locust, Gatling, or similar performance testing tools.
• Experience deploying performance tests on AWS EC2 or integrating them into CI/CD pipelines.
• Experience generating synthetic test data and managing database snapshots for performance testing.
• Understanding of key performance metrics, including latency, P95/P99 response times, throughput, error rates, CPU, memory, network, and file I/O.
• Basic understanding of database performance concepts such as indexing, connection pooling, and database locks.
• Ability to use monitoring and observability tools to analyze performance results and identify system bottlenecks.