Tech Lead - QA - Performance Testing

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.
• Strong communication, root-cause analysis, and fast learning ability.

Nice to have

• Deeper ETL / data pipeline background.
• BI tools such as Power BI, Tableau, Cognos, or similar.
• k6, Grafana, Datadog, Application Insights, or other observability tools.
• Cloud experience (Azure preferred).

Education

Bachelor’s degree in Computer Science, Engineering, or equivalent experience.

All your information will be kept confidential according to EEO guidelines.