About The Position

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.

Requirements

  • 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 Haves

  • 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).

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.
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