Performance Test Engineer

DATAMAXIS•Okemos, MI

51d

About The Position

Primary Job Responsibilities: 1. Design and lead comprehensive performance testing strategies to validate system behavior under load, stress, and peak conditions. Align these strategies with business requirements and project goals 2. Create, configure, and execute complex test scripts in JMeter to simulate real-world usage scenarios and workload patterns. Optimize and troubleshoot scripts to achieve accurate and reliable performance assessments. 3. Utilize Dynatrace for continuous performance monitoring, tracking key application metrics (response time, throughput, resource utilization) and diagnosing issues in real-time to support proactive performance management. 4. Integrate performance testing and monitoring tools within CI/CD pipelines using Jenkins, ensuring that performance issues are identified and addressed early in the development lifecycle. 5. Perform in-depth capacity planning analysis, determining optimal infrastructure requirements to handle projected workloads and recommending strategies for scaling applications in Kubernetes environments. 6. Use Bitbucket for version control of test scripts, configurations, and related documentation, fostering effective collaboration and change tracking within performance engineering teams. 7. Collaborate with development, DevOps, and operations teams to troubleshoot performance bottlenecks and recommend tuning or architectural changes to improve application performance and scalability. 8. Deploy, monitor, and troubleshoot applications running in Kubernetes clusters, ensuring efficient use of resources, autoscaling configurations, and resilience under load. 9. Generate detailed performance reports and dashboards that present test results, analysis, and insights for various stakeholders, including senior management and engineering teams. 10. Conduct root cause analysis for complex performance issues, using Dynatrace and other diagnostics tools to trace issues to specific components, services, or resource configurations. 11. Initiate proactive approach to advocate for performance engineering best practices, contributing to a culture of continuous improvement in performance testing and monitoring processes. 12. Document test strategies, configurations, tuning recommendations, and lessons learned, ensuring continuity and knowledge sharing within the team. These responsibilities ensure a strong focus on performance optimization, scalability, and reliability in modern cloud-native environments, making use of advanced testing, monitoring, and automation capabilities. 13. Actively participate in PI planning sessions to align performance goals and establish testing strategies and set realistic performance targets. Ensure all the dependencies are identified, documented and addressed.

Requirements

Position requires a bachelor’s degree in computer science or engineering and seven years of experience in applications and systems performance testing, monitoring and evaluation and five years’ experience in application development.
Will accept any suitable combination of education, training, or experience.
Strong hands-on experience with JMeter for creating complex test scripts and scenarios.
Proficiency with Dynatrace or similar APM tools for real-time monitoring, diagnostics, and root cause analysis
Ability to interpret performance data to identify trends, bottlenecks, and areas for optimization
Experience managing and optimizing performance in Kubernetes environments, autoscaling, and tuning applications for efficient use of cluster resources.
Knowledge on versioning and CI/CD integration tools like Bitbucket and Jenkins for maintaining test suites
Advanced knowledge of DB/SQL/Linux and experienced working in agile work environment.
Effective communication skills and ability to resolve complex problems and use independent judgment.

Responsibilities

Design and lead comprehensive performance testing strategies to validate system behavior under load, stress, and peak conditions. Align these strategies with business requirements and project goals
Create, configure, and execute complex test scripts in JMeter to simulate real-world usage scenarios and workload patterns. Optimize and troubleshoot scripts to achieve accurate and reliable performance assessments.
Utilize Dynatrace for continuous performance monitoring, tracking key application metrics (response time, throughput, resource utilization) and diagnosing issues in real-time to support proactive performance management.
Integrate performance testing and monitoring tools within CI/CD pipelines using Jenkins, ensuring that performance issues are identified and addressed early in the development lifecycle.
Perform in-depth capacity planning analysis, determining optimal infrastructure requirements to handle projected workloads and recommending strategies for scaling applications in Kubernetes environments.
Use Bitbucket for version control of test scripts, configurations, and related documentation, fostering effective collaboration and change tracking within performance engineering teams.
Collaborate with development, DevOps, and operations teams to troubleshoot performance bottlenecks and recommend tuning or architectural changes to improve application performance and scalability.
Deploy, monitor, and troubleshoot applications running in Kubernetes clusters, ensuring efficient use of resources, autoscaling configurations, and resilience under load.
Generate detailed performance reports and dashboards that present test results, analysis, and insights for various stakeholders, including senior management and engineering teams.
Conduct root cause analysis for complex performance issues, using Dynatrace and other diagnostics tools to trace issues to specific components, services, or resource configurations.
Initiate proactive approach to advocate for performance engineering best practices, contributing to a culture of continuous improvement in performance testing and monitoring processes.
Document test strategies, configurations, tuning recommendations, and lessons learned, ensuring continuity and knowledge sharing within the team.
Actively participate in PI planning sessions to align performance goals and establish testing strategies and set realistic performance targets. Ensure all the dependencies are identified, documented and addressed.