技术负责人 - QA - 性能测试
Tech Lead - QA - Performance Testing
Sutherland
人工智能。自动化。云工程。高级分析。对商业领袖而言，这些是成功的关键因素。对我们而言，它们是我们核心的专业领域。
我们与全球知名品牌合作。我们通过领先的科技和卓越的业务流程，为他们带来独特的价值主张。
我们在人工智能和其他关键技术领域下，已创造了200多项专利的独特发明。借助我们先进的产品和平台，我们推动数字化转型，优化关键业务运营，重塑体验，开创新解决方案，所有都通过无缝的“即服务”模式提供。
对于每家公司，我们为其业务、所合作的人以及所服务的客户带来新的钥匙。我们定制经过验证且快速的公式，以适应他们的独特基因。我们结合人类专业知识和人工智能，开发数字化学反应。这解锁了新的可能性、变革性的成果和持久的关系。
Sutherland
释放数字表现力。实现可衡量的结果。
职位概述
我们正在寻找一名性能工程师，在SAFe环境中设计并执行针对网页应用、BI工作负载和ETL/数据模型的性能测试。该职位需要在Apache JMeter、JavaScript/TypeScript、Python和Playwright方面有扎实的实战经验，用于自定义网页、BI和ETL性能脚本。需要有Azure DevOps流水线经验。快速学习能力至关重要。需要熟练使用GitHub Copilot；熟悉MCP者优先。
职责
· 设计、执行和分析网页应用、BI报表/仪表板及ETL/数据模型的性能测试 —— 使用JMeter（负载、压力、持续、尖峰）进行网页测试，使用自定义Playwright/Python脚本进行BI和ETL测试 —— 并将SLA转化为可测量的阈值。
· 验证ETL流水线和数据模型性能 —— 作业运行时间、数据量处理、转换吞吐量以及下游报告影响。
· 评估BI性能 —— 报表/仪表板加载时间、查询响应、并发用户负载以及刷新/批量窗口。
· 将性能测试集成到Azure DevOps流水线中，包括自动化质量门禁、报告和发布准备检查。
· 识别瓶颈，发布清晰的发现结果，并与开发、QA、数据和运维团队协作。
· 参与SAFe活动（PI计划、冲刺计划、系统演示、检查与适应），并达成迭代/PI目标
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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.
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.