Performance Engineer

Location: St. Louis, MO (Final Interview Onsite)

Interview Mode: Onsite Interview

Client: Master Card/Apexon

• Define service-level objectives (SLOs), performance budgets, and latency/throughput targets across services.
• Architect and champion comprehensive distributed tracing strategies (Dynatrace, AWS X-Ray, etc.).
• Analyze application, platform, and cloud behavior using deep-dive techniques such as heap dumps, thread dumps, flame graphs, GC logs, network traces, and storage I/O profiling.
• Review service and system architectures for performance risks (e.g., synchronous hops, excessive dependencies, misconfigured connection pools, poor cache placement).
• Conduct and lead root-cause analysis for performance incidents in production and pre-production environments.
• Develop capacity models and performance baselines for services running across cloud environments.

• Application Layer:
  Spring Boot internals, JVM tuning, thread/heap management, concurrency debugging, GC optimization
• Container Runtime: PCF, Docker, container resource limits, CPU throttling, memory pressure
• Networking:
  Service-to-service hops, TLS overhead, DNS, routing, load balancer configs (F5, Nginx, ALB/NLB), service mesh performance
• Storage:
  Latency, IOPS constraints, distributed file system behavior
• Caching & Middleware:
  Redis, Hazelcast, NATS, Kafka, RabbitMQ configuration and throughput tuning
• Cloud Layer: AWS compute/storage/network performance, regional latency, cross-cloud traffic patterns