Due to nuclear site access/or export-controlled project requirements, this role requires candidates to be U.S. Citizens and not hold dual citizenship. Candidates must also be willing to work on W2.
Travel Required: No
Work Model: Onsite
Bill Rate: $54/hr
Hours: 40 hours/week
We are seeking an experienced HPC Storage & Data Management Engineer to design, administer, and optimize storage environments within an enterprise-scale, AWS-based high-performance computing platform. This role partners closely with infrastructure and digital technology teams to support global engineering simulation users.
Key Responsibilities
- Storage Architecture & Optimization: Manage home directories, high-performance scratch storage, project storage, and archive tiers, aligning data placement with workload performance requirements.
- Quota & Capacity Management: Administer user and project storage quotas, monitor utilization, and provide capacity forecasts.
- File Permissions & Access Management: Manage permissions and access control lists across NFS/SMB environments, ensuring consistent access for Linux HPC and Windows VDI users.
- Cost Visibility & Reporting: Support storage cost benchmarking and reporting within the AWS environment.
- Data Lifecycle Management: Define and enforce policies for active, scratch, cold, and archived data, including automated tiering and expiration workflows.
- Archiving & Retention: Develop and implement archival standards aligned with engineering simulation data retention requirements.
- Storage Governance: Establish shared team and project folder structures, document standard operating procedures, and communicate storage usage guidelines.
- AI/ML Readiness: Support data standards that make engineering simulation data structured and accessible for AI/ML workloads.
TECHNICAL SKILLS
Must Have
- Demonstrated ability to develop and document standard operating procedures.
- Experience administering HPC storage in a production environment.
- Experience with quota management systems and storage capacity planning.
- Expertise in high-performance parallel/distributed file systems such as Lustre, GPFS/IBM Spectrum Scale, BeeGFS, WekaIO, or similar.
- Proficiency in storage tiering, data lifecycle management, and archival tooling.
- Strong experience with NFS and SMB/CIFS dual-protocol permission and ACL management.
Nice to Have
- Experience in AWS or hybrid cloud storage environments, including S3, FSx for Lustre, and EFS.
- Experience working within a DevOps or collaborative Infrastructure as Code model.
- Familiarity with engineering simulation data, such as CFD or FEA, and associated file size and storage patterns.
- Familiarity with the Slurm job scheduler in the context of scratch and burst storage.