We were happy to see the theme "Partnerships and Collaborations" because this proposal is about working in community to discuss how we may sustainably manage student labor.* (*"student" is used broadly; any novice hired to support our work in hands-on technical data services.) While data support has a long tradition, the sexiness of Data Science has raised awareness of the power in data and we now have both more customers looking for sophisticated solutions as well as more variably-skilled students seeking practical experience. When we take on interns or student workers, we are training the next generation of data professionals, but how can we keep up with their training/mentoring & also assure the quality of our services? (especially on students' schedules!?) We seek collaborators to identify commonalities in the technical data support needs and services among our varied institutions. Further, we are interested in discussing our models for managing student technical support staff; sharing successes and challenges. This may lead us to a community/network model (ie Data Carpentries) to support cross-institutional mentoring and managers wrangling iterations of novices in the service of their data support mission. Potential discussion areas: -Who is the intended recipient of our services? Who else might need help? How/how well are we currently satisfying these needs? Can they be categorized generically? -How are we distributing the workload? How are we finding suitable student staff (both literally and figuratively)? How are we managing them, their training, and their projects? -Is/how is this knowledge or set of practices captured for future temporary data support staff (students)? -Is it reasonable/useful to construct a community of practice among supervisors? Can it be self sustaining? Panelists: -Paula Lackie (chair) -Carleton College -Deborah Wiltshire -UK Data Archive -Stephanie Labou -UCSD