The future social metaverse traffic demands over 5G and beyond (B5G) networks can be supported by efficiently placing the user plane function (UPF). Third-generation partnership project (3GPP) standard mandates that all application traffic in B5G core network must be routed through a UPF before it can reach its destination. In this regard, we propose an optimal UPF placement algorithm, referred to as Decomposed Minimum Power UPF Placement (DeMPUP), which selects the minimum power consumption path from the next-generation node B (gNB) to the edge server on the overlay backbone network. Coupled with the optimal path selection, the proposed algorithm also identifies the optimal node over which the UPF would be placed. We provide a power consumption model of the core network with a corresponding joint non-linear programming (NLP) minimization problem for UPF placement. Owing to the high complexity of the formulated NLP, for enhanced scalability over large B5G cores, we decompose the problem into two sub-problems. The first sub-problem identifies a set of feasible paths commensurate with UPF power requirement, and the subsequent sub-problem selects the optimum path among the feasible paths that minimizes the power consumption. The selected path also uniquely identifies the node to place the UPF for minimum power consumption. Analysis of DeMPUP shows that it executes in linear time and scales linearly with the number of nodes. Experimental results reveal significant power reduction for different network sizes.