DataDirect Networks

High-performance storage for unstructured data

QA Engineer 2

Performance TestingConfirmed live in the last 24 hours

Full-time$110k - $140k /yrRemote

About the Job

Requirements

Python experience, with at least two years of scripting experience and familiarity with basic asynchronous and task-queue concepts; Celery experience is a plus.
Working knowledge of Ansible, including writing or modifying playbooks and roles.
Basic SQL skills with PostgreSQL.
Linux fundamentals, including filesystems, networking, and processes.
Exposure to continuous integration and continuous delivery tools such as GitHub Actions or similar.
Understanding of block, file, and object storage concepts, and willingness to learn benchmarking tools such as FIO, IOR, and mdtest.

Responsibilities

Build and extend 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.
Perform 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 and roles for cluster setup, health checks, installation, and configuration.
Contribute to Celery-based task orchestration for running I/O workloads in parallel.
Execute and troubleshoot storage benchmarks, including FIO, IOR, mdtest, IO500, and WARP.
Write Python scripts to parse results, generate manifests, and normalize metrics.
Help maintain the PostgreSQL results schema and Grafana dashboards.
Assist with test reporting integration.
Debug test failures and flaky pipeline runs across protocols.
Contribute new benchmark profiles using YAML workload definitions for review.
Work with developers to validate fixes and assess feature performance impact.

Desired Qualifications

Prior exposure to Redis, RabbitMQ, or another message queue.
Experience with Grafana or another dashboarding tool.
Basic Node.js knowledge.
Internship or project experience with performance testing or storage systems.
Familiarity with monitoring and metrics tools such as Prometheus and Grafana.
Celery experience.

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).

About the Company

DataDirect Networks

High-performance storage for unstructured data

DDN provides high-performance data storage systems and software for data-intensive environments, including unstructured data, HPC, and AI workloads. Its products combine hardware and software to manage the data lifecycle, with A³I for GPU-optimized AI, EXAScaler as a parallel file system, IntelliFlash hybrid arrays, and Infinia for fast inference. The company differentiates itself through a dedicated focus on HPC/AI storage, close collaboration with NVIDIA, and a strategy of expanding software-defined storage and file systems via acquisitions. Its goal is to help customers scale data storage and AI workloads efficiently across enterprises, government, academia, and cloud providers.

Company size: 1,001-5,000
Company stage: Growth Equity (Venture Capital)
Total funding: $309.9M
Headquarters: Los Angeles, CA
Founded: 1998

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