With the rapid development of electric vehicle charging stations, effective management of them has become challenging due to the high uncertainty of electric vehicles, the pricing mechanisms of charging stations, and their coupling with distribution networks. To address these challenges, this paper proposes a two-stage framework for energy management at charging stations. In the first stage, a resource allocation model considering the profits of distribution systems, charging stations, and electric vehicle users is established based on the aggregate feasible power regions of charging stations. The aggregate feasible region is obtained based on the combination of Minkowski summation and the data-driven method, which can preserve the privacy of electric vehicle data and reduce the computational burden. In the second stage, a novel hierarchical pricing mechanism is developed, which encompasses both the clearing price between charging stations and distribution networks and the retail electricity price between charging stations and electric vehicle users. Notably, charging stations participate in the power clearing of distributed networks based on the aggregate feasible power region, while a two-stage robust pricing strategy is established between electric vehicle users and charging stations. The model is finally optimized through a distributed coordination mechanism with a clear physical interpretation. The simulation results show that the proposed aggregation method enables charging stations to achieve a total economic profit at least 1.76 % higher than three competitive methods. The hierarchical pricing mechanism allows charging stations to achieve total economic profits 18.60 % and 2.94 % higher than those in the centralized dispatch and price-taker modes, respectively, while simultaneously reducing operating costs for the distributed network by 25.96 % and 27.99 %.