Rfcuny
Facilities Data Specialist Intern
New York, NY · Intern · Internship
Sponsorship not specifiedDetected 30 days ago
Data AnalysisCustomer SupportResearchBIM
About the role
- Thank you for considering a career with the Research Foundation of The City University of New York (RFCUNY).
- The team at RFCUNY is made up of dedicated, talented professionals committed to providing the services that allow CUNY researchers, faculty, and staff to focus on their intellectual curiosity and scientific discoveries.
Requirements
- Must be a CUNY student
- Pursuing a Bachelor's degree in facilities management, architecture, or IT
- Must be available for at least 14 hours a week
- Ability to adapt to a fast-paced work environment and changing needs and priorities
- Ability to multi-task, meet deadlines, and work independently
- Has essential data entry and data analysis skills, has familiarity with spreadsheets, and has familiarity with relational databases
Skills
- The primary current use of the system is space management and facilities maintenance.
- Archibus integrates geospatial information (CAD, BIM, Maps) with a comprehensive facilities relational database.
Compensation
- $17.50 per hour
Benefits
- RFCUNY Employee Benefits and Accruals
- RFCUNY Benefits
Company info
- We are pleased that you are interested in exploring opportunities to join RFCUNY.
Equal opportunity
- The Research Foundation of the City University of New York is an Equal Opportunity/Affirmative Action/Americans with Disabilities Act/E-Verify Employer.
- It is the policy of the Research Foundation of CUNY to provide equal employment opportunities free of discrimination based on race, color, age, religion, sex, pregnancy, childbirth, national origin, disability, marital status, veteran status, sexual orientation, gender identity, genetic information, marital status, domestic violence victim status, arrest record, criminal conviction history, or any other protected characteristic under applicable law.
This listing is sourced directly from Rfcuny's careers page and normalized into a canonical job model.