Lead Performance & Observability Engineer
Intercontinental Exchange6 months ago
Responsibilities
- Own performance engineering strategy, testing standards, tooling, and reporting across multiple critical platforms.
- Lead deep-dive performance investigations of CPU-bound, multithreaded Java systems across JVM, operating system, and hardware layers.
- Perform scalability modeling, capacity projections, critical-path segregation, and validation of architectural performance improvements.
- Design and operate observability frameworks covering metrics, distributed tracing, continuous profiling, health scoring, alerting, and Grafana dashboards.
- Build custom metrics exporters and automated post-test analysis pipelines that correlate load-test and observability data.
- Design performance test harnesses and production-representative workloads, and tune JVM thread pools, garbage collection, and heap allocation.
- Act as a technical liaison across performance, development, infrastructure, operations, architecture, and project management teams.
- Mentor peers and establish standards for validating AI-generated performance analysis and tooling before production use.
Requirements
- Bachelor’s degree or equivalent in Computer Science, Engineering, or a related field.
- 8+ years of experience in performance engineering, performance testing, or Java development in high-volume, low-latency transactional systems.
- Deep expertise in JVM internals, including heap dumps, thread dumps, garbage collection logs, and memory profiling.
- Proficiency with Java and scripting languages such as Python, Groovy, or Linux shell.
- Experience with scalability analysis, critical-path analysis, event-driven or message-based architectures, and performance validation.
- Hands-on experience with observability stacks covering metrics, distributed tracing, and continuous profiling.
- Experience with Prometheus, VictoriaMetrics, Grafana, custom metrics exporters, dashboard governance, and alerting rules.
- Experience with JMeter, Gatling, or custom load-generation harnesses and representative production workloads.
- Experience building automated reporting pipelines that combine load-test results with observability data.
- Experience with Kafka, IBM MQ, or equivalent event-pipeline technologies.
- Strong verbal and written communication skills and the ability to present findings to technical and non-technical stakeholders.
- Proficiency with AI coding and analysis tools such as GitHub Copilot, Claude, or Cursor for performance-related tasks.
Tech Stack
Categories
About Intercontinental Exchange
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