We present a dynamic programming based solution to a stochastic reachability problem for a controlled discrete-time stochastic hybrid system. A sum-multiplicative cost function is introduced along with a corresponding dynamic recursion which quantifies the probability of hitting a target set at some point during a finite time horizon, while avoiding an obstacle set during each time step preceding the target hitting time. In contrast with earlier works which consider the reach and avoid sets as both deterministic and time invariant, we consider the avoid set to be both time-varying and probabilistic. Optimal reach-avoid control policies are derived as the solution to an optimal control problem via dynamic programming. A computational example motivated by aircraft motion planning is provided.