Data represents an increasingly critical strategic asset for companies of all sectors and sizes. Without a solid foundation of Analytics engineering, one risks having poor quality data, manual and fragmented processes, unreliable analysis, and long delivery times. Fortunately, there are tools that help implement the best Analytics engineering practices efficiently and at scale. One of these is dbt (data build tool), an open-source platform that simplifies the transformation, documentation, and testing of data models. The main focus of the thesis is to implement a modern pipeline solution that incorporates all best practice of analytics engineering. The inclusion of an analytics engineer within a data team represents a new paradigm in data-driven organizations.