This paper introduces an environment for distributed video transcoding based on Grid computing infrastructure and Internet Backplane Protocol storage infrastructure. A model for scheduling jobs with respect to location of data in distributed storage is introduced for optimal processormance. We describe our abstraction library libxio providing a uniform access interface to both local files and data stored on IBP. Modifications of video tools done based on this library in order to work with IBP are being presented as well as a system that controls an overall distributed encoding process and helps scheduling system to schedule jobs in agreement with the distribution of data in IBP. Two pilot groups that use this system for preparing video content for streaming are mentioned.