Rotary-wing Unmanned Aerial Vehicles (commonly referred to as drones) are a versatile platform that can be used for many data collection applications including emergency response, environmental monitoring, surveillance, and many others. In this work, we investigate how to plan efficient paths that minimize mission completion time for drone data collection where the drone must rendezvous with a moving ground vehicle that cannot stop and wait for the drone. More importantly, we address the limited onboard energy storage issue by adapting drone speed. We propose a mixed-integer nonlinear program solution to solve this problem optimally and provide various alternative solutions. We evaluate these approaches in extensive simulations using real drone characteristics to highlight their trade-offs. We show that our proposed solutions can greatly reduce mission completion time when compared to other baseline approaches and demonstrate the importance of drone speed adaptation in path finding for drones. We also prototype our solution on a physical drone testbed to show how the problem setup can be applied practically.