Smart logistics management faces the challenge of effectively handling massive heterogeneous data. In this paper, we outline the design and implementation of a big data management service platform for smart logistics. First, we propose an overall system design approach based on business, functionality, and data requirements. Then, we utilize a distributed architecture comprising data collection, storage, computation, and application modules to achieve efficient processing of big data. Simultaneously, the design adheres to principles of service-oriented architecture and decoupling, while employing intelligent algorithms to enhance planning and forecasting capabilities. Testing confirms the platform's stable and reliable operation, meeting the needs of smart logistics management. This research provides valuable insights for constructing an efficient and intelligent big data-driven logistics management system.