Emerging to satisfy the needs of consumers in the e-commerce era, omni-channel retailing is the integration of the online channel and the offline store network with the key features of channel integration and inventory sharing. As such, the omni-channel retailer faces more challenging problems of pricing and order fulfillment compared with the pure e-commence retailer. With the omni-channel features, we study the joint dynamic pricing and (cross-channel) order fulfillment problem of an omni-channel retailer with a network of physical stores and fulfillment centers facing limited initial inventory and no replenishment opportunity in a finite selling season. The classical multinomial logit (MNL) choice model is used to characterize the customer demand with the above omni-channel features. Then, the omni-channel joint dynamic pricing and order fulfillment policy (OPFP) is identified based on the optimal solution of the deterministic relaxation to the stochastic control formulation of the original problem. Theoretically, we demonstrate that the proposed approximation policy is asymptotically optimal. We examine some variants of this OPFP to address the problem under various practical constraints and show that they maintain sufficiently good performance. In addition, we show that the proposed OPFP can yield a lower average order fulfillment cost than the heuristic order fulfillment policy that chooses the bricks-and-mortar store with the lowest fulfillment cost. We also find that the improved performance of the re-optimization policy can be offset by the loss of sales volume transfer between channels for large-scale problems.