Snowflake is a cloud-based data warehouse that offers a number of advantages over traditional on-premises data warehouses, including scalability, performance, and cost-effectiveness. Snowflake is also well-suited for ETL (extract, transform, and load) workloads, as it provides a number of features that make it easy to move data from disparate sources into a single, centralized repository. In this session, we will cover the end-to-end process of building an ETL (Extract, Transform, Load) pipeline in Snowflake. We will start by discussing the key components of an ETL pipeline and how they work together. Then, we will walk through a sample ETL project, from extracting data from external sources to loading it into Snowflake and transforming it into a format that is ready for analysis.