Performance Test Engineer
Core
Design and execute performance test plans, scenarios, and workload models to evaluate software applications for scalability, stability, and responsiveness under varying loads.
Role type
Performance Test Engineer
Builds
Performance test scripts, reports, and CI/CD integrated quality gates
Domain
Software Quality Engineering / Performance Engineering
Required skills
Apache JMeter, load/stress/spike/scalability testing, scripting (Groovy, Java, JavaScript, Python), correlation, parameterization, dynamic token extraction, SQL, CI/CD integration, performance monitoring (New Relic, Grafana, Prometheus, Dynatrace), root cause analysis
Preferred skills
high-traffic API testing, workload modeling, capacity planning, bottleneck diagnosis (CPU, memory, GC, DB, network), cloud-based testing, Docker, Kubernetes, microservices, log analysis, production troubleshooting
Technologies
Apache JMeter, Jenkins, GitHub Actions, Git, Jira, Azure DevOps, New Relic, Grafana, Prometheus, Dynatrace, Docker, Kubernetes, SQL, REST, HTTP/HTTPS, Groovy, Java, JavaScript, Python
Responsibilities
Design and run performance test plans, scenarios, and workload models based on business requirements. Develop and maintain Apache JMeter performance test scripts. Configure JMeter components and set ramp-up periods, concurrent users, throughput targets, and pacing. Apply parameterization and correlation to manage dynamic values, session IDs, and authentication tokens. Test REST APIs, web applications, and distributed systems under load, stress, spike, endurance, and scalability conditions. Analyze response times, throughput, error rates, concurrent users, and percentile results. Monitor application and infrastructure resources, including CPU, memory, databases, and network utilization. Identify performance bottlenecks and work with development and infrastructure teams to investigate root causes. Integrate performance tests into CI/CD pipelines using Jenkins or similar tools. Prepare performance test reports documenting observations, bottlenecks, and optimization recommendations. Validate application behavior during peak loads and long-duration runs. Collaborate with developers, database administrators, DevOps engineers, and product teams to improve performance. Maintain reusable scripts, test data, workload profiles, and performance testing documentation.
