When organizations decentralize data product ownership, as in the data mesh paradigm, each domain team optimizes for its immediate analytical needs, underinvesting in the cross-domain generality that enables organization-wide reuse. We formalize this as a simultaneous-move game in which N domains choose quality (q) and generality (g). Generality creates positive externalities but is privately costly. The Nash equilibrium generality gap is increasing in the number of domains and the value of cross-domain analytics. Under plausible parameter configurations, a corner solution obtains in which no reusable silver layer emerges organically, a condition we term the data mesh trap. Technical debt from narrow products grows quadratically in N. An illustrative calibration suggests non-trivial organizational welfare losses under plausible enterprise parameters. We derive within-model conditions under which centralized, federated, and hybrid governance regimes dominate, and we identify the information asymmetries and transaction costs that complicate implementation. The model provides a formal foundation for empirical research on decentralized data governance.

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