Research Storage Engineer Senior

How to Apply

A cover letter and resume are important submissions for the hiring team to get a sense of your experience. In the cover letter, within one page or less, please let us know how this role aligns with your career aspirations and skills. Submit both a cover letter and resume as one file.

Competitive salary available based on qualifications, experience, and education of the selected candidate.

Information and Technology Services (ITS) supports U‑M faculty, researchers, staff, and students in their use of technology to teach, learn, research, and work, and be leaders in their fields. We are dedicated to creating cohesive digital experiences and promoting university‑wide innovations. ITS’s mission is to be trusted enablers of technology for the U‑M community.

The Advanced Research Computing (ARC) organization has an exciting opportunity to employ a Storage Engineer Senior. This position will report to the Research Computing Manager and will be part of a team responsible for operating, supporting, and building world‑class storage platforms for research. The role includes maintaining and supporting research data stored on ARC storage systems and utilizing storage technologies and software development techniques to design and implement storage automation, resource management, and trend analysis.

ARC is the University of Michigan’s research IT provider specializing in High Performance Computing (HPC), AI/Machine Learning, high‑speed networking, storage, and other technologies to accelerate the research mission of the institution.

For more information about ARC, please visit our website: (Use the "Apply for this Job" box below). and for more information about ITS, please visit our website: .

• Install and support storage software
• Create documentation for users and administrators
• Apply software patches
• End‑to‑end performance tuning of the data platforms
• Keep abreast of new methods, functionality, and releases to enhance capability
• Provide support to users of the service
  • Provide training and documentation on best practices to power users and the general user base
  • Assist users in troubleshooting complex use cases
  • Evaluate improvements to user experience
• Support the development of internal ARC resources for management of ARC storage services, such as provisioning workflows, user offboarding or metadata analysis.
• Assist in building and maintaining an inventory of faculty consumed resources on the Private Cloud environment
• Work with other ARC and affiliated staff to support computational research across the University
• Stay abreast of application technology trends in storage solutions and environments (technology system management methods, etc.)

• Bachelor’s degree in computer science, engineering or an equivalent combination of education and experience
• Strong understanding of scripting languages such as bash/shell, and one of Perl or Python
• 4 or more years in managing a production Linux environment
• Strong understanding of configuration management and system provisioning methods and tools
• Strong understanding of security practices in a shared environment
• Strong understanding of storage deployments using NSF version 4 with Kerberos, NFS version 3 and CIFS including file permissions
• Understand Unix/Linux TCP/IP networking
• Understanding of SQL
• Understanding of modern data analytics tools
• Proficiency in troubleshooting, verbal and written communication, interpersonal communication with others, and prioritization when faced with multiple requests and projects
• Ability to creatively improve workflows and processes
• Ability to work self‑sufficiently and participate in a larger distributed support structure

• Understanding of specific regulatory frameworks such as HIPAA, Controlled Unclassified Information (CUI), NIST 800‑171
• Experience in a related role requiring customer service, confidentiality, timeliness, organization, prioritization, troubleshooting, and working independently to successfully design services and workflows
• Experience with Starfish, Spectrum Discover, Komprise, GUFI, or other data lifecycle, discovery, or workflow tools
• Exp…