Performance Engineer - AWS Cloud Platform

Description :

- Design and execute comprehensive Load, Stress, Endurance, Spike, and Volume tests using tools like Apache JMeter, LoadRunner, or NeoLoad.

- Build robust performance test frameworks tailored for microservices hosted on EKS.

- Conduct end-to-end performance benchmarking across API, database, and UI layers.

AWS Cloud and EKS Focus :

- Work directly with AWS services such as EKS, EC2, S3, RDS, CloudWatch, and Application Load Balancer (ALB) during test planning and execution.

- Simulate real-world distributed load in EKS-based environments and evaluate auto-scaling behaviors, node performance, and pod-level resource usage.

- Collaborate with DevOps to ensure test pods are deployed and scaled properly in Kubernetes clusters.

Monitoring & Observability :

- Use tools like Grafana, CloudWatch, Prometheus, Datadog, and New Relic to monitor performance metrics in real time.

- Analyze system behavior through dashboards, logs, and alerts to identify performance bottlenecks and degradation.

- Capture pod-level metrics (CPU, memory, network) from Kubernetes namespaces and workloads under test.

CI/CD and Automation Integration :

- Integrate performance test suites into CI/CD pipelines using tools like Jenkins, GitHub Actions, or AWS CodePipeline.

- Ensure automated execution of performance tests as part of build validations and release gates.

Reliability & Caching Validation :

- Validate caching layers (Redis, CDN, Memcached) and their impact on response time under high load.

- Provide recommendations to improve system reliability, latency, and throughput using test results and observability data.

Must-Have Skills :

- 8+ years in Performance Testing & Engineering.

- Strong expertise with JMeter, Neo Load , or similar tools.

- Solid hands-on experience with AWS and especially EKS (pods, nodes, services, auto-scaling).

- Strong understanding of Kubernetes workloads, Helm charts, and config maps.

- Familiarity with monitoring and logging in cloud-native environments : Grafana, CloudWatch, Datadog, Prometheus.

- Basic scripting in Python, Shell, or Groovy.

- Experience in testing REST APIs, microservices, and containerized applications.

Nice-to-Have :

- AWS Certification (Cloud Practitioner, Developer Associate, or DevOps Engineer).

- Experience with Terraform, Helm, or Kustomize.

- Familiarity with chaos testing or resilience validation.

- Experience with service mesh performance.