Performance Quality Engineer
We are looking for a Performance Engineer with 5–8 years of experience in performance testing and engineering for large-scale, distributed, high-volume applications. The ideal candidate will have strong hands-on experience in performance testing, bottleneck analysis, capacity planning, observability, cloud-native technologies, and automation. Experience with payment processing or other high-transaction systems is preferred.
Essential functions
- Define and execute performance engineering strategies for scalable, high-throughput applications.
- Design and execute load, stress, endurance, spike, volume, and failover testing.
- Perform workload modeling, capacity planning, benchmarking, and scalability assessments.
- Identify and troubleshoot performance bottlenecks across application, JVM, database, middleware, OS, Kubernetes, and network layers.
- Analyze thread dumps, heap dumps, GC logs, CPU/memory utilization, database performance, and network latency.
- Conduct performance tuning and root-cause analysis in collaboration with development, architecture, SRE, and operations teams.
- Build reusable performance testing frameworks and integrate performance tests into CI/CD pipelines.
- Monitor and analyze application/infrastructure performance using tools such as Dynatrace, AppDynamics, Grafana, Prometheus, Splunk, or OpenTelemetry.
- Evaluate performance of Kubernetes, Docker, microservices, event-driven architectures, and cloud-native applications.
- Develop performance dashboards, automated reports, and proactive monitoring solutions.
- Provide performance recommendations during application design and code reviews.
- Support production performance incidents, capacity reviews, resiliency testing, and disaster recovery exercises.
Qualifications
- 5–8 years of experience in Performance Engineering, Performance Testing, SRE, Production Engineering, or Software Engineering.
- Strong hands-on experience with at least one performance testing tool: JMeter, LoadRunner, Gatling, k6, BlazeMeter, or Locust.
- Strong understanding of load, stress, endurance, spike testing, performance benchmarking, and capacity planning.
- Experience with Java, Python, or Go and scripting/automation.
- Strong knowledge of REST APIs, microservices, distributed systems, and CI/CD.
- Hands-on experience with Kubernetes, Docker, and at least one cloud platform (AWS/Azure/GCP).
- Strong Linux/Unix fundamentals, including CPU, memory, networking, and system performance analysis.
- Experience with application and infrastructure monitoring/observability tools such as Dynatrace, AppDynamics, Grafana, Prometheus, Splunk, or OpenTelemetry.
- Good knowledge of relational databases such as Oracle, MySQL, PostgreSQL, or SQL Server, including query optimization and performance tuning.
- Strong analytical and troubleshooting skills with experience performing performance bottleneck and root-cause analysis.
- Experience working with large-scale, high-transaction or distributed enterprise applications.
- Strong communication and collaboration skills.
Would be a plus
- Experience in FinTech/Payments or high-volume transaction systems.
- Knowledge of distributed systems, Kafka, IBM MQ, Hazelcast, and Spring Boot.
- Experience with JVM tuning, Kubernetes optimization, and OpenTelemetry.
- Hands-on with Terraform/Ansible and CI/CD performance integration.
- Exposure to FinOps, cloud cost optimization, and capacity forecasting.
- Experience with AI/GenAI for performance analysis or automated RCA.
We offer
- Opportunity to work on bleeding-edge projects
- Work with a highly motivated and dedicated team
- Competitive salary
- Flexible schedule
- Benefits package - medical insurance, sports
- Corporate social events
- Professional development opportunities
- Well-equipped office
About us
Grid Dynamics (NASDAQ: GDYN) is a leading provider of technology consulting, platform and product engineering, AI, and advanced analytics services. Fusing technical vision with business acumen, we solve the most pressing technical challenges and enable positive business outcomes for enterprise companies undergoing business transformation. A key differentiator for Grid Dynamics is our 8 years of experience and leadership in enterprise AI, supported by profound expertise and ongoing investment in data, analytics, cloud & DevOps, application modernization and customer experience. Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the Americas, Europe, and India.
