In recent years, so-called lakehouses have emerged as a new type of data platform that intends to combine characteristics of data warehouses and data lakes. Although companies started to employ the associated concepts and technologies as part of their analytics architectures, little is known about their practical medium- and long-term experiences as well as proven architectural decisions. Additionally, there is only limited knowledge about how lakehouses can be utilized effectively in an industrial context. Hence, it remains unclear under which circumstances lakehouses represent a viable alternative to conventional data platforms. To address this gap, we conducted a case study on a real-world industrial case, in which manufacturing data needs to be managed and analytically exploited. Within the scope of this case, a dedicated analytics department has been testing and leveraging a lakehouse approach for several months in a productive environment with high data volumes and various types of analytical workloads. The paper at hand presents the results of our within-case analyses and focuses on the industrial setting of the case as well as the architecture of the utilized lakehouse. This way, it provides preliminary insights on the application of lakehouses in industrial practice and refers to useful architectural decisions.