Fostering an open, shared, and secure unified data market is a pivotal task for advancing the construction of Digital China and for serving the new forms of the smart economy. The new data infrastructure serves as the core carrier for supporting data element circulation and directly determines the effectiveness of data value release. Currently, the development of China's data infrastructure still faces deep-seated challenges. The root cause lies in the longstanding constraints of the "impossible trinity" of security, cost-effectiveness, and compatibility, alongside difficulties in synergizing existing resources with new development. This study summarizes the fundamental engineering challenges in constructing new data infrastructure, and elaborates on the vision, basic principles, and theoretical support elements for its development. Moreover, it innovatively proposes a "cloud‒network integrated hyper-convergence" architecture for data infrastructure, based on the theory of polymorphic intelligent network environment. Additionally, it employs a technical logic of "elementalizing network resources" and "dynamic resource aggregation," empowered by AI-enabled generative networks, to generate dedicated, scenario-adaptive network modalities on demand. Drawing on live network demonstrations, this study elaborates on the design philosophy and key technologies of the new data infrastructure architecture, and summarizes a synergistic construction model of "stock efficiency + incremental optimization." Practice shows that this architecture can provide an engineering solution to the "impossible trinity" and the stock‒increment synergy dilemma. Finally, the study proposes recommendations covering engineering advancement, technological innovation, platform support, disciplinary development, and institutional safeguards, aiming to provide theoretical and practical insights for building a nationally unified data market.