G18 - Software Quality Engineer

About this role

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. Originally posted on Himalayas

Skills and categories