Performance Automation QA
Project description
We are seeking an experienced Performance Automation QA Engineer with deep expertise in performance testing, test automation, and scalability engineering. The ideal candidate will design, implement, and execute performance test strategies using Apache JMeter, ensuring system reliability, responsiveness, and stability under varying load conditions. This role requires strong analytical capability, hands-on scripting experience, and a solid understanding of distributed systems and performance engineering principles.
Responsibilities
- Design and develop performance test strategies, plans, and frameworks aligned with business and technical requirements Build, maintain, and execute automated performance test scripts using Apache JMeter Conduct load, stress, spike, endurance, and scalability testing Analyze test results and identify performance bottlenecks across application, database, and infrastructure layers Collaborate with developers, DevOps, and architecture teams to diagnose and resolve performance issues Integrate performance testing into CI/CD pipelines (e.g., Jenkins, GitLab CI) Monitor application performance using tools such as Dynatrace, AppDynamics, or New Relic Develop and maintain custom plugins, scripts, or utilities (Groovy, Java, or Beanshell in JMeter) Provide detailed performance reports, including KPIs (throughput, latency, error rates, resource utilization) Define and enforce performance SLAs, SLOs, and benchmarking standards
SKILLS
Must have
- 8+ years of experience in performance testing and engineering Create, execute, and analyse performance test cases using a Java-based customized UI built on top of JMeter. Generate, manage, and maintain test data to support consistent and reliable performance testing. Expert hands-on experience with Apache JMeter (test plan design, distributed testing, parameterization, correlation) Proficiency in scripting languages (Java, Groovy, Python, or similar) Experience with API performance testing (REST/SOAP) Solid understanding of HTTP/HTTPS protocols, TCP/IP, and web architectures Experience with CI/CD integration and automation frameworks Familiarity with containerized environments (Docker, Kubernetes) Strong skills in performance analysis and tuning (thread dumps, heap analysis, GC tuning) Experience with monitoring and APM tools
Nice to have
Experience with other tools (LoadRunner, Gatling, k6) Knowledge of cloud platforms (AWS, Azure, GCP) and performance testing in cloud-native environments Understanding of microservices architecture and distributed systems Experience with message queues (Kafka, RabbitMQ) performance testing ISTQB or relevant performance testing certifications
