What are the responsibilities and job description for the Sr. Performance Test Engineer position at USM Business Systems?
Job Overview
We are seeking an experienced Sr. Performance Test Engineer to join an Agile engineering team responsible for developing and enhancing enterprise healthcare applications. The ideal candidate will bring strong expertise in performance testing, LoadRunner, Google Cloud Platform, workload modeling, performance tuning, APM, and CI/CD integration.
This role requires a technically strong and confident professional who can lead performance engineering initiatives, work closely with cross-functional teams, engage directly with clients, and take ownership of critical performance issues and escalations.
Key Responsibilities
Design and execute performance, load, stress, scalability, and endurance testing strategies for enterprise applications.
Develop realistic workload models and performance test scenarios based on business requirements and production usage patterns.
Create and execute complex performance test scripts using LoadRunner or equivalent enterprise performance testing tools.
Analyze application, database, infrastructure, and cloud performance to identify bottlenecks and scalability issues.
Work extensively with Google Cloud Platform (Google Cloud Platform) environments and evaluate application performance across services such as GKE, Cloud Run, Compute Engine, and Pub/Sub.
Perform performance tuning across application, database, infrastructure, and cloud layers.
Utilize APM and observability tools such as Dynatrace, AppDynamics, Google Cloud Monitoring/Stackdriver, or similar platforms for performance analysis and root-cause identification.
Integrate performance testing into CI/CD pipelines and support continuous performance validation throughout the SDLC.
Analyze performance test results, identify trends, and provide actionable recommendations for optimization.
Lead performance war rooms, critical incident discussions, and performance review sessions.
Collaborate with development, DevOps, architecture, database, and infrastructure teams to resolve complex performance issues.
Communicate technical findings and recommendations effectively to clients, leadership, and engineering teams.
Challenge assumptions and drive data-driven decisions related to application performance and scalability.
Mentor team members and drive accountability across performance engineering initiatives.
Mandatory Skills & Qualifications
10 years of experience in Performance Testing, Performance Engineering, or a related field.
Strong hands-on experience with LoadRunner or equivalent enterprise performance testing tools.
Strong experience with Google Cloud Platform (Google Cloud Platform).
Understanding of cloud architecture, scalability, capacity planning, and performance optimization.
Deep expertise in workload modeling and performance analysis.
Strong understanding of performance tuning across application, database, infrastructure, and cloud environments.
Hands-on experience with APM tools such as Dynatrace, AppDynamics, Google Cloud Monitoring/Stackdriver, or similar.
Experience integrating performance testing into CI/CD pipelines.
Strong scripting, troubleshooting, analytical, and problem-solving skills.
Ability to interpret performance metrics and translate findings into actionable recommendations.
Exposure to AI/ML applications in performance testing, including predictive analytics, anomaly detection, and intelligent workload modeling.
Leadership & Client-Facing Expectations
Highly articulate, confident, and effective communicator.
Proven ability to lead performance war rooms and critical incident discussions.
Strong experience working directly with clients, handling escalations, and conducting performance reviews.
Ability to challenge technical assumptions and promote data-driven decision-making.
Demonstrated ability to lead teams, influence stakeholders, and drive accountability.
Experience working with distributed onshore/offshore teams.
Nice-to-Have Skills
Experience with JMeter, Gatling, or k6.
Knowledge of Docker and Kubernetes.
Experience with Google Cloud Platform observability and monitoring tools.
Exposure to AI-powered performance testing tools and platforms.
Experience with healthcare applications or enterprise SaaS platforms.
Strong understanding of modern SDLC and Agile methodologies.
Salary : $50