Tech Lead - QA - Performance Testing

About the job

Company Description About Sutherland

Artificial Intelligence. Automation. Cloud engineering. Advanced analytics. For business leaders, these are key factors of success. For us, they’re our core expertise.

We work with iconic brands worldwide. We bring them a unique value proposition through market-leading technology and business process excellence.

We’ve created over 200 unique inventions under several patents across AI and other critical technologies. Leveraging our advanced products and platforms, we drive digital transformation, optimize critical business operations, reinvent experiences, and pioneer new solutions, all provided through a seamless “as a service” model.

For each company, we provide new keys for their businesses, the people they work with, and the customers they serve. We tailor proven and rapid formulas, to fit their unique DNA. We bring together human expertise and artificial intelligence to develop digital chemistry. This unlocks new possibilities, transformative outcomes and enduring relationships.

Sutherland

Unlocking digital performance. Delivering measurable results.

Job Description 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.

Qualifications 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.

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