Job
Description
JD For Performance Test Engineer Key Responsibilities: Develop, enhance, and maintain Locust performance scripts using Python Design scenarios simulating real-world usage and traffic patterns Perform script enhancement and parameterization to ensure robustness and reusability Execute performance test scripts in containerized environments using Docker and Kubernetes Manage Locust execution on Kubernetes clusters Automate Locust script execution through CI/CD pipelines Collaborate with DevOps and Development teams to integrate performance testing into the CI/CD lifecycle Analyze test results and generate performance reports, including throughput, latency, response time, and error rates Identify application bottlenecks, perform root cause analysis, and provide tuning recommendations Work with AWS (or other cloud platforms) to deploy, scale, and monitor performance tests in cloud-native environments Write, execute, and optimize complex SQL queries along with enhancement and readability of stored procedures for performance testing back-end systems Hands-on with SQL Server – Must be able to read, modify, and tune stored procedures Exposure to Postgres DB is a plus Develop and maintain performance test strategies and test plans Define KPIs, SLAs, workload models, and success criteria Guide the team on best practices and drive performance engineering mindset Must-Have Qualifications: Proven experience with Locust and Python for performance testing Working knowledge of Microservices Hands-on with Kubernetes and Docker – particularly with running Locust in containerized environments Experience integrating performance tests into CI/CD pipelines Strong AWS (or cloud) experience, with performance test deployments on cloud infrastructure Solid understanding of SQL Server – including stored procedures, query tuning, and DB performance analysis Strong background in performance test planning, strategy creation, and execution Good-to-Have Skills: Exposure to Postgres DB Familiarity with monitoring and observability tools like Prometheus, Grafana, CloudWatch, Datadog, etc. Basic knowledge of application performance monitoring (APM) tools. Show more Show less
