The Research Data Storage Analyst reports to the Associate Director, Research Computing Systems and Storage and works as part of a team that supports the hardware and system level software on the university's TIGRESS centralized high performance computing systems and other research computing systems.
Responsibilities include working with faculty, vendors, and IT staff to design and specify research computing systems and storage used in data intensive research, as well as installing and administering those systems.
The analyst helps end-users to troubleshoot system level problems with software, data, and job submission and also teaches workshops and mini-courses in research data archival and management related topics as needed by the university's research community.
The position requires working closely with colleagues in OIT, the Library, the Office of the Dean for Research, and technical staff in university departments to provide timely and creative support for long term data storage and retrieval for research computing. This individual works both with teams and independently, requiring only general supervision.
Consulting with faculty, vendors, and IT staff to design and specify research computing storage systems to support long term archival and retrieval of research data.
Installing, maintaining, and administering research computing storage and retrieval systems.
Applying and developing best practices for installation, configuration, and operation of data intensive research computing systems both on-premises and in the cloud.
Analyzing and troubleshooting complex system level problems with software, data, and job submissions.
Providing instruction and conducting workshops on research data archival and retrieval methods and strategies as needed.
Working with campus partners including library staff and research computing staff to develop a training curriculum and user-friendly interfaces for conducting and archiving data intensive research.
Providing multi-level support for the large user base of the data intensive computing resources.
Installing, maintaining, and supporting data archival and retrieval software and schedulers on these systems.
Monitoring system and network health and performance.
Administering both local and global storage available to our research computing and archival systems.
Managing and maintaining vendor relationships.
Advising faculty and researchers on data intensive research and big data issues.
Keeping abreast of emerging technologies related to data archival and retrieval
Using scripting and programming tools (bash, Python, and/or Perl) and performing basic debugging.
Developing and maintaining documentation related to data intensive research systems and storage.
Providing off-hours, on-call support for HPC systems on a rotating basis.
When provided access to personal, proprietary, and/or otherwise confidential data, maintains such data in the strictest confidence and follows procedures to ensure the privacy, security, and proper use of data.
Expertise with big data system administration, installation, and troubleshooting including Hadoop, MySQL, and PostgreSQL.
Experience managing computational and storage hardware including parallel filesystems like GPFS and/or Lustre, as well as ‘cloud’ storage systems.
Experience managing systems that process and store restricted use, confidential, and personally identifiable data in a secure and private manner.
Strong oral and written communication skills.
Ability to respond promptly and professionally to customer requests.
Minimum of five years of experience as a big data system administrator.
Ability to apply skills and knowledge to solve routine and moderately complex problems in a Linux operating system environment.
Demonstrated successes working in a collaborative environment as well as independently.
Ability to learn new systems beyond area of core knowledge.
The ability to communicate effectively with a diverse user base having varied levels of technical proficiencies.
Proactively seeks information and ideas from peers, supervisors, and customers.
Ability to handle multiple priorities.
A bachelor’s degree in science, information technology, mathematics, computer engineering, or a related computational field required or a Masters/Ph.D. in computer science or other related field with a strong computational focus preferred.
Princeton University is an Equal Opportunity/Affirmative Action Employer and all qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity or expression, national origin, disability status, protected veteran status, or any other characteristic protected by law. EEO IS THE LAW
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