DevRabbit IT Solutions
Website:
devrabbit.com
Job details:
About your role
As a QA Automation Lead for Performance testing at Juniper Square, you will define the performance engineering strategy for the organization. You will ensure our systems can handle hyper-growth and peak traffic events through proactive modeling, automated gating, and deep architectural analysis.
What you’ll do
- Review functional and non-functional requirements, technical design documents, and provide meaningful feedback to identify performance risks early.
- Design, develop, and execute performance, load, and stress tests for web and backend systems.
- Use AI to analyze production traffic patterns and automatically generate representative performance scripts in Locust or JMeter that mirror real-world user behavior
- Build and maintain performance test scripts using Python, primarily leveraging Locust (tool-agnostic mindset, but Locust experience is a strong plus)
- Collaborate closely with development, QA, DevOps, and SRE teams to define performance benchmarks, SLAs, and acceptance criteria.
- Analyze test results to identify bottlenecks related to application code, APIs, databases, infrastructure, or third-party dependencies.
- Produce clear and actionable performance test reports, highlighting trends, risks, and recommendations for optimization.
- Integrate performance tests into CI/CD pipelines and support continuous performance testing practices.
- Monitor application performance during releases and contribute to capacity planning and scalability discussions.
- Lead performance engineering best practices and help shift performance testing left in the SDLC.
Qualifications
- Education: Bachelor's degree in Computer Science, or equivalent professional experience.
- Experience: 7-10 years in Software Quality Assurance, with at least 5 years focused on performance, load, stress, and endurance testing.
- Performance Testing: Strong hands-on experience designing and executing performance test strategies for web applications and APIs with an ability to read architectural diagrams and identify potential single points of failure.
- Programming Skills: Strong proficiency in Python, with the ability to write clean, maintainable, and scalable test code.
- Tools and Systems: Experience with performance testing tools such as Locust (preferred), JMeter, Gatling, or similar
- Metrics & Analysis: Solid understanding of performance metrics (response time, throughput, latency, error rates, resource utilization) and profiling techniques.
- APIs & Backend: Hands-on experience testing REST APIs and backend services under load.
- CI/CD : Experience designing and owning the Performance Gate in the CI/CD pipeline, ensuring automated performance regressions are caught before reaching production.
- Observability & Profiling: Advanced skills in using APM tools (e.g., Datadog, New Relic, or Dynatrace) and profiling tools to pinpoint code-level bottlenecks, memory leaks, and thread contention.
- Data Strategy: Experience managing large-scale, sanitized test data sets required for high-volume performance execution without skewing cache results.
- Infrastructure & Cloud: Deep experience with AWS infrastructure (EC2, Lambda, RDS, ELB), and containerization (Docker, Kubernetes)
- Test Process: Experience in performance test plans, scenarios, workload models, and test data strategies.
- Soft Skills: Excellent analytical and problem-solving abilities, attention to detail, and the ability to work independently within Agile development teams.
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