Job Description Strong experience in Performance Engineering / Performance Testing roles with proven expertise in identifying, analyzing, and resolving application performance bottlenecks. Hands-on experience designing and executing Load, Stress, Endurance, Scalability, and Capacity Testing for distributed and enterprise applications. Strong proficiency in performance testing tools such as JMeter, Load Runner, Gatling, Neo Load, or equivalent. Hands-on scripting experience using Python or Groovy for test automation, performance framework development, and data analysis. Experience working with Docker containers and Kubernetes (K8s) environments, including performance validation of containerized and microservices-based applications. Strong understanding of application architecture, APIs, web services, databases, and microservices performance characteristics. Experience using monitoring and observability tools such as Dynatrace, App Dynamics, Splunk, Prometheus, Grafana, or similar platforms for performance analysis and troubleshooting. Ability to analyze JVM, application, database, infrastructure, and network-level metrics to identify root causes of performance issues. Good understanding of CI/CD pipelines and integration of performance testing into automated release processes. Experience collaborating with Development, QA, Platform Engineering, and DevOps teams to establish performance benchmarks and scalability strategies. Strong knowledge of Linux/Unix environments and command-line troubleshooting. Excellent analytical, problem-solving, and communication skills with the ability to present performance findings and optimization recommendations to technical and business stakeholders. Nice to Have: Exposure to cloud platforms such as AWS, Azure, or GCP. Experience with Performance Engineering in Kubernetes-based production environments. Basic understanding of DevOps practices, release engineering, and site reliability concepts. Knowledge of Java/Spring Boot application performance tuning.