Senior Storage Platform Engineer

Nvidia

Confirmed live today High trust
Hybrid

Quick summary

Work type
Hybrid
Location
Santa Clara, CA
Salary
$168,000–$270,250 / yr
Posted
4 days ago
Freshness
Confirmed live today

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $186k
This role $219k
$120k most similar roles pay here $286k

This role pays more than 75% of similar roles. Most pay $151,000–$222,000 — the shaded band above. At the midpoint, this role pays about $219k versus about $186k for comparable roles.

Based on 240 similar postings.

Employer

About Nvidia

Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing

Nvidia currently has 929 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 915 roles with salary data.

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View all roles at Nvidia

At a glance

TL;DR · Senior Storage Platform Engineer

As a Senior Storage Platform Engineer, you will join the team responsible for designing, deploying, and operating storage platforms that power EDA FARM, software engineering, AI/ML teams, and engineering workflows at scale. You will manage the full lifecycle of multi-vendor infrastructure including NetApp ONTAP, Pure Storage FlashArray or FlashBlade, Cloudian HyperStore, and DDN systems. Your daily work involves building automation pipelines, implementing Infrastructure as Code using Ansible and Terraform, and developing CI/CD workflows for configuration deployments. You will integrate storage with CMDB platforms, observability stacks like Prometheus and Grafana, and self-service portals. The role requires expertise in protocols such as NFS, SMB, iSCSI, NVMe-oF, S3, and Lustre, alongside proficiency in Python or Go. You will solve complex infrastructure challenges by providing scalable, automated storage solutions for high-performance computing and research environments.

What you'll do

  • Lead the end-to-end deployment of multi-vendor storage systems including NetApp, Pure Storage, Cloudian, and DDN.
  • Design and implement Infrastructure as Code frameworks using Ansible or Terraform to automate provisioning and lifecycle operations.
  • Build and maintain CI/CD pipelines for automated, validated storage configuration deployments.
  • Integrate storage platforms with CMDBs, observability stacks, and configuration management tools for asset tracking and monitoring.
  • Develop self-service portals and tooling to allow engineering teams to provision storage on demand.
  • Manage day-2 operations including capacity planning, firmware updates, performance tuning, and root cause analysis.
  • Champion GitOps practices to ensure all storage configurations are tracked and managed without manual overrides.

What we're looking for

  • 8+ years of hands-on experience with enterprise storage systems in large-scale production environments.
  • Deep knowledge of at least three platforms: NetApp ONTAP, Pure Storage FlashArray/FlashBlade, Cloudian HyperStore, or DDN.
  • Strong command of storage protocols including NFS, SMB, iSCSI, NVMe-oF, S3, and Lustre.
  • Proven experience building infrastructure automation with Ansible, Terraform, or equivalent IaC tools.
  • Proficiency in Python, Go, or similar languages to build reusable tooling.
  • Experience integrating storage systems with CMDB platforms and observability stacks like Prometheus, Grafana, Splunk, or Datadog.
  • Solid experience with CI/CD platforms (GitHub Actions, Jenkins, GitLab CI) and Git-based workflows.
  • MS Degree in Computer Science or equivalent experience.
  • Experience in HPC, AI/ML, or large-scale research computing environments (preferred).
  • Experience building self-service storage provisioning workflows (preferred).
  • Experience with containerization technologies such as Docker, Mesosphere DCOS, or Kubernetes (preferred).
  • Experience contributing to or maintaining internal developer tools or platform APIs (preferred).

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