I work in machine learning and also in data engineering, and for most of my career the data engineering title was for people doing everything in the lifecycle outside of R&D workflows (building the models/model architecture itself). It's only very recently differentiated to MLE/DE, and even that is far from being a standard.

The skillset is largely the same, but with some specialized knowledge for ML data work.