Lakehouse Performance Engineer

IBM

Quick summary

Work type
On-site
Location
Austin, TX
Posted
8 days ago

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Similar $182k
$126k most similar roles pay here $232k

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Listed pay typically runs $1,000,000–$1,000,000 across 8 roles with salary data.

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TL;DR · Lakehouse Performance Engineer

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As a Senior Performance Engineer at IBM in Austin, you will join the watsonx.data team to focus on enhancing the performance and cost-efficiency of their GPU-accelerated data lakehouse platform. Your daily tasks include running industry-standard benchmarks, building customer-representative workloads, ensuring reproducibility, and operationalizing price-performance metrics. You’ll also develop telemetry pipelines, create dashboards for trend analysis, manage regression gates in CI/CD, and conduct root-cause analyses using profilers like Nsight and async-profiler. Additionally, you will own the lifecycle of dedicated performance environments, build infrastructure-as-code for test fleets, and maintain benchmark harnesses. The role requires strong programming skills in Python, Go, or Java, experience with modern analytics engines, and familiarity with GPU-accelerated data processing tools like RAPIDS and Velox.

Skills

Python Go Terraform Ansible Helm Linux perf ftrace eBPF Nsight async-profiler pprof Prometheus Grafana Kubernetes OpenTelemetry TPC MLPerf ClickBench LST-Bench FinOps CI/CD

What you'll do

  • Run and maintain reproducible benchmarks for watsonx.data configurations.
  • Build workload suites that reflect real customer query mixes and data volumes.
  • Ensure every published performance result is fully reproducible end-to-end.
  • Develop and operate the benchmark harness platform for standardized perf experiments.
  • Manage capacity and utilization of dedicated performance lab environments.
  • Operate performance regression gates in CI/CD to triage and verify fixes.

What we're looking for

  • 8+ years of professional software engineering experience with at least 2 years in performance engineering.
  • Strong programming skills in Python, Go, Java, and shell scripting; familiarity with modern automation tools.
  • Hands-on experience with Linux performance tooling, profilers, and query plan analysis.
  • Infrastructure-as-code fluency in Terraform, Ansible, Pulumi, or Helm for provisioning test environments.
  • Experience with GPU-accelerated data processing and multi-tenant performance lab operations.
  • Familiarity with vector search, retrieval-augmented generation (RAG), and AI inference/training performance.

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