Data lakes aim to avoid vendor lock-in and enable interoperability between different query engines on a single copy of data. While early data lakes were only collections of files in various formats, they have since evolved to incorporate some features traditionally associated with relational databases. Today, Apache Parquet is the de facto standard file format for relational data in data lakes. This standardization is fundamental to interoperability, but it comes at the cost of physical data independence because query engines integrate tightly with Parquet. As a result, adoption of novel approaches in the areas of file formats, access paths, and storage media has been limited. We propose the Active Data Lake architecture as a way to restore physical data independence and demonstrate its potential experimentally through three example optimizations.