Architectural Knowledge Management (AKM) is concerned with capturing, sharing and reusing the architectural knowledge. Design rationale, which constitutes the reasoning behind the software architecture, is a key component of architectural knowledge. Existing AKM support has been dedicated to capture and reuse of design rationale, however, automated and proactive knowledge-sharing has not been addressed well in the community. Hence, in this research, we address the issue of architectural knowledge sharing. We propose an enterprise-wide recommender system to enable proactive knowledge-sharing by extending a traditional guidance model with data mining techniques. The viability is demonistrated using synthetic data and Linkdin users of software architects. In particular, we focus on recommending an architect with items such as architects with similar interests, similar issues and alternatives. The key benefits of this approach are: improved reuse of design rationale in order to avoid several repetitive steps for deciding on architectural issues and enhancing knowledge transfer between global projects and departments. We believe that a similar recommender system could also be applied to other areas of software engineering.