The transition from linear to circular value-preserving models poses significant challenges, particularly in the context of Reverse Logistics. Variability in returned products in terms of time and quality and logistical complexities referring to decentralized and central factories hamper implementation. While digitalization offers the potential to optimize these processes, many companies lack a structured, scalable, and interoperable approach for integrating digital tools into Reverse Logistics. Moreover, the concept has largely been neglected and limited to managing returns from quality and warranty claims. Existing Enterprise Architecture Models frequently fall short in addressing challenges such as product condition and variability, independence from proprietary systems, and the integration of multiple Circular Economy (CE) strategies thereby constraining their practical applicability. The present paper aims to address these gaps by proposing a generic, vendor-independent, data-driven architecture model that enables companies to implement efficient, sustainable Reverse Logistics in alignment with CE goals. This model fulfills the pressing need for practical frameworks that support interoperability, reuse of existing IT infrastructure, and comprehensive process transparency. Consequently, organizations will be empowered to implement smart Reverse Logistics and to meet regulatory demands, resource efficiency targets, and consumer expectations for sustainable products. Furthermore, the model should serve to meet national and supranational environmental protection targets.