Performance Test Engineer

Title: Performance Test Engineer . make sure consultant should be available for the calls in EST (Eastern) Hours.

Location: Remote

Contract: Jan End (Likely Extension)

Start: Immediate

Responsibilities:

• Own the

  performance test strategy & plan

  (load, stress, spike, soak, scalability, failover).
• Model traffic for

  ad-supported streaming

  (burstiness, fan-out, cache hit/miss, cold-start, geo distribution, p95/p99/p999).
• Build

  automated load frameworks & scripts

  (preferably

  Locust/Python

  ;

  JMeter

  where appropriate). Parameterize data, correlations, and think-time.
• Orchestrate

  distributed load generation

  (cloud workers, containerized runners) to simulate

  45M concurrent

  at scale.
• Integrate with

  observability/APM

  (metrics, logs, traces) to correlate system bottlenecks across app, JVM/GC, Akka dispatchers, network, caches, and databases.
• Produce

  capacity models & SLAs/SLOs

  dashboards; run

  performance gates

  in CI/CD.
• Partner with DevOps & developers to recommend

  tuning

  (thread pools, connection pools, GC, autoscaling, cache strategies, DB indexes/queries).
• Document test design, scenarios, results, and

  clear remediation plans

  .

Technology Proficiency Needed:

• Load tools

  :

  Locust (Python)

  ,

  JMeter

  ; (nice to have: k6, Gatling).

• Scripting & automation

  : Python (core), Bash; infra spin-up via Terraform/Docker/Kubernetes for load farms.

• Metrics/Tracing

  : CloudWatch, OpenTelemetry, Prometheus/Grafana; log analysis pipelines.
• Familiarity with

  Java service

  behaviors (Maven/Gradle pipelines, JVM/GC basics);

  Akka

  concepts are a plus.

What makes you a great fit

• 3–5+ years in

  performance engineering

  for

  large-scale, low-latency

  distributed systems; streaming/ad-tech exposure is a plus.
• Demonstrated success

  hitting strict SLAs

  (p95/p99 latency) under millions of users/RPS.
• Strong

  Python

  and test-automation skills; ability to build maintainable, reusable test frameworks.
• Experience designing

  realistic workload models

  , synthetic data generation, and

  distributed

  load execution in cloud.
• Analytical, communicates crisply with stakeholders, converts data into

  prioritized recommendations

  .