In the ideal limit of infinite resources, multi-tenant applications are able to scale in/out on a Cloud driven only by their functional requirements. While a large Public Cloud may be a reasonable approximation of this condition, small scientific computing centres usually work in a saturated regime. In this case, an advanced resource allocation policy is needed in order to optimize the use of the data centre. The general topic of advanced resource scheduling is addressed by several components of the EU-funded INDIGO-DataCloud project. In this contribution, we describe the FairShare Scheduler Service (FaSS) for OpenNebula (ONE). The service must satisfy resource requests according to an algorithm which prioritizes tasks according to an initial weight and to the historical resource usage of the project. The software was designed to be less intrusive as possible in the ONE code. We keep the original ONE scheduler implementation to match requests to available resources, but the queue of pending jobs to be processed is the one ordered according to priorities as delivered by the FaSS. The FaSS implementation is still being finalized and in this contribution we describe the functional and design requirements the module should satisfy, as well as its high-level architecture.