The Public Utility Data Liberation (PUDL) Project, developed by Catalyst Cooperative, aims to make valuable public energy data readily accessible and user-friendly for those working to decarbonize the energy system. Initially using Python and pandas, the team faced challenges such as a burdensome process for adding new data sources, lack of parallelism, and difficult access to interim outputs from the ETL pipeline. To overcome these issues, they adopted Dagster, an open-source data engineering solution that enabled them to create a declarative approach, simplify their workflow, and accelerate development iteration cycles. With Dagster, Catalyst Cooperative can now add new data sources with relative ease, publish cleaned versions of tables, and make interim assets available to users, ultimately improving their ability to scale up the project and integrate more diverse datasets.