Senior Performance Test Engineer

Key Responsibilities

• Own end-to-end performance test lifecycle: requirements/NFR discovery, workload modeling, scripting, execution, analysis, reporting, and sign-off.

• Define performance test strategy and standards (load, stress, spike, endurance/soak, scalability, capacity) aligned to SLAs/SLOs.

• Develop and maintain reusable performance test assets:

• JMeter test plans (correlation, parameterization, assertions, timers, controllers)

• LoadRunner scripts and scenarios (VuGen/Controller/Analysis) where applicable

• Execute distributed tests using BlazeMeter and/or LoadRunner; manage environments, test data, and load agents.

• Design realistic workload models: concurrency, ramp patterns, pacing, think time, arrival rate, and test data variation.

• Integrate performance testing into CI/CD (e.g., Jenkins/GitLab/Azure DevOps) with automated baseline and regression runs.

• Perform root-cause analysis by correlating results with telemetry:

• Dynatrace: service flow, distributed tracing, CPU/memory, JVM/.NET, DB calls, thread pools

• Splunk: SPL queries, log correlation, dashboards, alerting for error patterns and anomalies

• Establish performance baselines, monitor trends across releases, and define performance gates for release readiness.

• Partner with developers, SRE/infra, DB and network teams on tuning (app configs, DB queries, caching, connection pools, GC, scaling).

• Provide clear stakeholder communications: summaries for leadership + technical deep dives for engineering teams.

• Mentor junior engineers and contribute to best practices, templates, and knowledge base.

Required Qualifications

• 6–10 years of hands-on experience in performance testing / performance engineering.

• Strong expertise in Apache JMeter (advanced scripting and test design).

• Experience with BlazeMeter for test execution and reporting and/or Micro Focus LoadRunner suite.

• Strong observability skills with:

• Dynatrace (APM, distributed tracing, dashboards, problem analysis)

• Splunk (SPL searches, dashboards, correlation of logs with performance symptoms)

• Strong understanding of application architectures: web, APIs (REST/SOAP), microservices, messaging basics.

• Working knowledge of performance metrics: throughput (RPS/TPS), latency percentiles (p95/p99), error rate, saturation points, capacity limits.

• Scripting/automation ability in one or more: Java, Groovy, Python, JavaScript.

• Strong documentation, reporting, and stakeholder management skills.