In the current era of data-driven innovation, the value of data can be significantly enhanced by facilitating its dissemination. In this context, the data mesh concept has gained popularity in recent years. Data Mesh includes domain experts who design so-called data products. It is imperative that all parties involved have trust in these data products. This applies in particular to data subjects who share their data, data owners who create the data products, and data consumers who use them. To establish such trust, privacy approaches are key. Due to the decentralized and distributed nature of data mesh, however, traditional privacy strategies cannot be applied. To address this issue, we present PROTON, a concept that facilitates the handling of PRivacy-cOmpliant daTa prOducts by desigN. PROTON is based on three pillars: a comprehensive description model for privacy requirements, an extended creation process that adheres to these requirements when compiling data products, and a refined access process for verifying compliance prior to data sharing. The practical applicability of PROTON is illustrated by means of a real-world application scenario that has been devised in collaboration with domain experts from our industry partner.