Application Engineer II - HPC Storage & Data Management Engineer

You’ll look after the storage behind a large cloud-based high-performance computing platform that supports about 1,500 engineers worldwide running simulations. You’ll manage how data is stored and where it lives, from fast working space to long-term archive, set and enforce storage limits and file permissions, and keep an eye on usage and cost in AWS. You’ll also set the rules for how data moves from active use to archive and help get simulation data organized so it’s ready for AI and machine learning. You’ll work closely with the Digital Technology (DT) team. RESPONSIBILITIES

• Manage and optimize the full HPC storage topology, including home directories, high-performance local scratch/compute, project storage, and archive tiers, and ensure data is placed to match workload performance requirements
• Administer and enforce per-user and per-project storage quotas; monitor utilization trends across the user base and provide capacity forecasting inputs to the HPC Principal Engineer and the Digital Technology (DT) team
• Manage file permissions and access control lists (ACLs) across multi-protocol (NFS/SMB) environments, ensuring consistent access governance for both Linux HPC and Windows VDI users
• Contribute to storage cost benchmarking and reporting, providing data-driven insight into storage spend within the AWS environment
• Define and enforce data lifecycle policies governing the progression of data through active, scratch, cold, and archive states; implement and maintain automated tiering and expiration workflows
• Lead the definition and implementation of an engineering simulation data archival standard, aligned with the broader engineering simulation data retention strategy
• Partner with the DT team to define and maintain collaborative team and project folder structures, and establish and communicate standard work for shared HPC storage use
• Support the organization’s initiative to define engineering simulation data standards so data is structured and accessible for AI/ML workloads

• Since this role involves access to U.S. export-controlled information, candidates must be able to obtain authorization for that access from the U.S. Government. Final offers are contingent on receiving this authorization.

The client you will be working for is a Fortune 500 Energy and Industrial Technology Company. This opportunity will give you experience in the energy transition sector with a company that is a globally recognized leader in power generation, wind energy, electrification, and grid solutions - and one of the most storied industrial brands in the world.