This work provides a finite-time stable disturbance observer design for the discretized dynamics of an unmanned vehicle in three-dimensional translational and rotational motion. The dynamics of this vehicle is discretized using a Lie group variational integrator as a grey box dynamics model that also accounts for unknown additive disturbance force and torque. Therefore, the input-state dynamics is partly known. The unknown dynamics is lumped into a single disturbance force and a single disturbance torque, both of which are estimated using the disturbance observer we design. This disturbance observer is finite-time stable (FTS) and works like a real-time machine learning scheme for the unknown dynamics.