Job Description & Details
This is a hands-on performance engineering gig for a massive financial services enterprise currently merging two major reservation platforms. You won't be writing manual test cases here; you will be directly responsible for ensuring the system doesn't melt down under the pressure of millions of daily consumer transactions.
What You'll Actually Be Doing
Your day-to-day will revolve around building complex load-test scenarios and hammering APIs and event-driven architectures to see where they break. You'll spend a lot of time analyzing latency percentiles, tracking down sneaky memory leaks or database bottlenecks, and figuring out throughput limits before real users hit them. Because this is tied to a platform merger, you'll be partnering closely with core engineering teams to feed them data so they can optimize their code.
The Core Tech Stack
You absolutely must have deep, production-level experience with enterprise load-testing tools like k6, JMeter, Gatling, or Locust. If you've only run basic script playbacks, you will struggle here—they need someone who can script complex user journeys, simulate heavy concurrent loads, and handle HTTP, API, and WebSocket traffic. Knowing how to read APM metrics and trace bottlenecks across a distributed stack is non-negotiable for this role.
Interview Expectations
Expect the hiring manager to throw a scenario at you like, "An API endpoint's p99 latency spikes drastically under a load of 5,000 requests per second while average latency remains flat; walk me through how you isolate where the bottleneck is." They aren't looking for a textbook definition of p99; they want to hear your methodical approach to analyzing thread pools, database connection saturation, and network latency. They might also ask you to write a quick script or conceptualize how you would test a real-time WebSocket connection under heavy concurrency to see how you structure your test data.
Application Advice
Skip the generic QA buzzwords and make sure your resume immediately highlights your actual metrics—mention the scale of the systems you've tested, the peak RPS you've simulated, and the tools you used to do it. Ensure keywords like "k6", "JMeter", "latency percentiles", "throughput", and "WebSocket traffic" are front and center so you easily clear the initial ATS filters and land directly on the engineering lead's desk.