ETL stands for extraction, transformation, and loading, in other words, for the data warehouse (DW) backstage. The main focus of our exposition here is the practical application of the ETL process in real world cases with extra problems and strong requirements, particularly performance issues related to population of large data warehouses. In a context of ETL/DW with strong requirements, we can individuate the most common constraints and criticalities that one can meet in developing an ETL system. We will describe some techniques related to the physical database design, pipelining, and parallelism which are crucial for the whole ETL process. We will propose our practical approach, “infrastructure based ETL”; it is not a tool but a set of functionalities or services that experience has proved to be useful and widespread enough in the ETL scenario, and one can build the application on top of it.