> Markdown version of [/jobs/ext/3344168-storage-architect](https://www.wearedevelopers.com/jobs/ext/3344168-storage-architect). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Storage Architect - **Company:** Thomas Jefferson National Accelerator Facility (Jefferson Lab) - **Location:** Newport News, VA, United States - **Experience:** Experienced - **Salary:** $118,400.0 - $186,500.0 - **Contract:** Permanent contract - **Skills:** Cloud Storage, Information Systems, Data Transmissions, Data Integrity, Extract Transform Load (ETL), Data Retention, Distributed File Systems, File Systems, Distributed Data Store, Distributed Systems, Storage Area Network (SAN), Internet Small Computer System Interface (ISCSI), Open Source Technology, Scientific Computating, Tape Libraries, Weka, Ceph (Software), High Performance Computing, HybridCloud, Storage Technologies, Information Technology, Data Management, Nvme - **Published:** September 17, 2026 - **Apply:** https://justjobs.com/main/sendform/8/8/28176/1/18328840?backUrl=%2Fcareer%2F18328840%2FStorage-Architect-Virginia-Newport-News ## About the Role * Required: Experience with hybrid cloud architectures for HPC workloads including cloud bursting and cross-site data movement over a WAN. * Preferred: Experience at a DOE national laboratory, research university HPC center, or equivalent scientific computing environment. * Required: 10 or more years HPC, scientific computing, large-scale distributed systems, or equivalent . * Required: 4 or more years designing and deploying high-performance parallel or distributed file systems at petabyte scale or beyond. * Required: Experience designing multi-tiered, highly available, and resilient storage architectures, including data staging, archival, and immutability strategies across distributed locations. * Required: Hands-on experience designing and deploying parallel or distributed file systems at petabyte scale or beyond in an HPC or scientific computing environment. * Required: Experience developing storage performance models, capacity planning frameworks, and total cost of ownership analyses at facility scale. Education * Required: Bachelor's Degree Computer Science, Information Systems, or other relevant information technology * Preferred: Master's Degree Computer Science, Information Systems, or other relevant information technology Experience and Education Exchange Education above the minimum may be substituted for experience. Relevant experience may not be substituted for education. Knowledge, Skills, and Abilities * Deep expertise in HPC storage technologies including parallel file systems, distributed file systems, object storage, cloud storage, tape libraries, SAN, and NAS. * Deep understanding of storage networking protocols and interconnects including Fibre Channel, iSCSI, NVMe-oF, and high-speed data transfer technologies relevant to high-throughput data workflows. * Evaluating and deploying commercial high-performance storage solutions (e.g. VAST, Weka, IBM Spectrum Scale) and open-source distributed file systems (e.g. Ceph, Lustre, DAOS) against performance, reliability, and cost requirements. * Familiarity with scientific data workflows including detector data ingest, MPI-IO access patterns, and HSM. (Preffered) * Familiarity with data integrity, encryption, and compliance requirements including FAIR data principles, data retention policies, and relevant federal data management standards. (Preffered) ## Description * Design Leadership: Lead the technical design of a multi-tiered, widely distributed storage system incorporating reliability, immutability, data integrity, and high-throughput performance across distributed locations. * Evaluate storage technologies: HPC platforms (VAST, Weka, Spectrum Scale), open-source file systems (Lustre, DAOS, Ceph), and cloud. Engage vendors, assess solutions, and develop analyses to support architecture and acquisition decisions. * Performance and Cost Modeling: Develop and validate models to predict storage performance, capacity, and total cost of ownership at scale. Define KPPs and benchmarking strategies to govern storage system selection and validation. * Metrics and Observability: Define initial SLOs and SLIs for storage performance and availability. Architect and implement monitoring and alerting solutions supporting design validation and future facility operations. * Establish Storage Team Framework: Define the operational framework and staffing plans for the future storage team, which will be responsible for the lifecycle management of the entire storage infrastructure.