Tech Lead - QA - Performance Testing

About this role

Role summary We are looking for a Performance Engineer to design and execute performance testing across web applications, BI workloads, and ETL/data models in a SAFe environment. The role requires strong hands-on experience with Apache JMeter, JavaScript/TypeScript, Python, and Playwright for custom web, BI, and ETL performance scripting. Azure DevOps pipeline experience is required. Ability to learn quickly is essential.

Hands-on use of GitHub Copilot is needed; familiarity with MCP is a plus. Responsibilities Design, execute, and analyze performance tests for web apps, BI reports/dashboards, and ETL/data models — JMeter (load, stress, soak, spike) for web, and custom Playwright/Python scripts for BI and ETL — and convert SLAs into measurable thresholds. Validate ETL pipeline and data-model performance — job runtime, data volume handling, transformation throughput, and downstream reporting impact.

Assess BI performance — report/dashboard load times, query response, concurrent user load, and refresh/batch windows. Integrate performance tests into Azure DevOps pipelines with automated quality gates, reporting, and release readiness checks. Identify bottlenecks, publish clear findings, and work with development, QA, data, and operations teams. Participate in SAFe ceremonies (PI Planning, Sprint Planning, System Demo, Inspect & Adapt) and deliver against iteration/PI goals.

Use GitHub Copilot (and MCP where available) to accelerate scripting, analysis, and documentation. Required skills 4–8 years in performance engineering or test automation with a strong performance focus. Strong JMeter experience: test plans, correlation, parameterization, assertions, distributed execution, and result analysis. Playwright + JavaScript/TypeScript and Python for custom client-side, BI, and ETL performance scripting.

Experience performance-testing web applications, BI tools, and ETL/data models. Azure DevOps experience: pipelines, CI/CD, test execution, and reporting. Working knowledge of SAFe and ability to operate in Agile Release Trains. Solid understanding of HTTP/APIs, data flows, and core performance metrics (latency, throughput, error rate, concurrency, job duration). Practical experience with GitHub Copilot; familiarity with MCP is a plus.