HPC Storage Architect: Scale & Data Movement

Susquehanna International Group; Philadelphia (Philadelphia County); On-site; USD 130,000 - 190,000; Full time

Job summary

A global quantitative trading firm is seeking an experienced HPC Storage Engineer to optimize storage and data movement within its high-performance computing environment. You will work on parallel filesystems and ensure reliable access to data for compute-intensive workloads. Ideal candidates will have hands-on experience with distributed filesystems, strong Linux skills, and a background in data-intensive applications. This is an opportunity to collaborate in a highly innovative environment focused on advanced quantitative research.

Qualifications

• Hands-on experience in production environments with parallel or distributed filesystems.
• Strong understanding of Linux systems administration.
• Proficiency in large-scale distributed systems (C++ preferred).

Responsibilities

• Design, deploy, and operate HPC storage systems and parallel/distributed filesystems.
• Own data movement workflows, including data ingest and archiving.
• Optimize filesystem performance for large-scale workloads.

Skills

Hands-on experience with parallel or distributed filesystems

Strong understanding of Linux systems administration

Experience with high-performance I/O optimization

Proficiency in large-scale distributed systems development

Troubleshoot performance and reliability issues

Experience with data transfer tools

Familiarity with object storage

Experience integrating storage with HPC schedulers

Background supporting data-intensive workloads

Job description

A global quantitative trading firm is seeking an experienced HPC Storage Engineer to optimize storage and data movement within its high-performance computing environment. You will work on parallel filesystems and ensure reliable access to data for compute-intensive workloads. Ideal candidates will have hands-on experience with distributed filesystems, strong Linux skills, and a background in data-intensive applications. This is an opportunity to collaborate in a highly innovative environment focused on advanced quantitative research.