The sky images captured nightly by the camera on the Vera C. Rubin Observatory’s telescope will be processed across facilities on three continents. Data acquisition will occur at the observatory's location on Cerro Pachón in the Andes mountains of Chile. A first copy of the raw image data set is stored at the summit and immediately transmitted via dedicated network links to the archive site and the US Data Facility at SLAC National Accelerator Laboratory in California. After a brief embargo period, the full dataset is transferred to the French Data Facility, where a third copy is maintained, and a partial dataset is transferred to the UK Data Facility. Over its 10-year operational period, beginning in late 2025, annual processing campaigns will be conducted by the three facilities on all images collected to date. Sophisticated algorithms will extract measurements of celestial objects from these images, producing science-ready images and catalogs. Data products resulting from these processing campaigns will be sent to SLAC for integration into a consistent Data Release, which will be made available to the scientific community through Data Access Centers in the US and Chile, as well as Independent Data Access Centers elsewhere. In this paper we present an overall view of how we leverage the tools selected for managing the movement of data among the Rubin processing and serving facilities, including Rucio and FTS. We will also present the tools we developed to integrate Rucio's data model and Rubin's Data Butler, the software abstraction layer that mediates all access to storage by pipeline tasks that implement science algorithms.
