Quick overview
Job description
Performance QE Engineer – distributed storage platform
DDN is hiring a Performance Automation Engineer to help build and extend our automated benchmarking infrastructure for the RED (Infinia) storage platform — covering S3, Block/CSI, and POSIX/HPC I/O paths, from test orchestration through results collection and dashboards.
The role requires knowledge & experience in storage performance testing, automation, and system‑level benchmarking, along with strong Python and Ansible skills to build scalable, repeatable test frameworks.
What You’ll Do
Work upon performance testing for a large‑scale distributed storage platform supporting S3 object storage, POSIX file systems, and block‑level protocols.
Write and maintain Ansible playbooks/roles for cluster setup, health checks, and install/configuration
Contribute to Celery-based task orchestration for running I/O workloads in parallel
Execute and troubleshoot storage benchmarks: FIO, IOR, mdtest, IO500, WARP
Write Python scripts for parsing results, generating manifests, and normalizing metrics
Help maintain the PostgreSQL results schema and Grafana dashboards
Assist with test reporting integration
Debug test failures and flaky pipeline run across protocols
Contribute new benchmark profiles (YAML workload definitions) under review
Work closely with developers to validate fixes and feature performance impact.
What You Bring
Python (2+ yrs): comfortable with scripting, basic async/task-queue concepts (Celery a plus)
Working knowledge of Ansible (writing/modifying playbooks and roles)
Basic SQL skills (PostgreSQL)
Linux fundamentals — filesystems, networking, processes
Exposure to CI/CD tools (GitHub Actions or similar)
Understanding of storage concepts (block/file/object) — willingness to learn benchmarking tools (FIO, IOR, mdtest)
Nice to Have
Prior exposure to Redis/RabbitMQ or any message queue
Grafana or other dashboarding tool experience
Node.js basics
Internship/project experience with performance testing or storage systems
Familiarity with monitoring and metrics tools (Prometheus, Grafana).
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