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. Originally posted on Himalayas