In the context of high penetration of electric vehicles (EVs) in the distribution network, the electricity consumption behaviour of EVs and the real-time electricity market exhibit high uncertainty. EV retailers need to establish reasonable retail pricing to reduce market risks, while ensuring their own profitability and the benefits of EV users. This paper proposes a two-stage robust pricing strategy for EV retailers based on the Stackelberg game, which considers various uncertain factors in the distribution network and satisfies the benefits of both EV users and EV retailers. First, a robust optimization model is established for EV retailers' day-ahead planning and real-time dispatch, considering the uncertainty of EVs and the real-time electricity market. Then, the robust optimization model is divided into a master problem and a sub-problem for two-stage optimization, which is solved iteratively using the Stackelberg game model and the column and constraint generation (CC&G) algorithm. Finally, simulations and verifications based on the IEEE33 benchmark model are conducted to demonstrate the effectiveness of the proposed strategy in the electricity market.