In order for any of the above to be possible (i.e. Data Analytics and Data Science), data actually has to be available. Analysts, Data Scientists, and Machine Learning Engineers need access to clean, organized, and timely data to do their work. This is where Data Engineering comes into the picture!
Sometimes referred to as Data Infrastructure or Data Architecture, Data Engineers help build the “data pipelines” that collect, store, update, and move data from one place to the next. These efforts are typically engineering-forward, in contrast to being analytical.
A common role in Data Engineering is: Data Engineer
So, in summary, folks in Data Engineering help build the infrastructure for data to be accurately collected, so that folks in Data Science and Analytics actually have data to work with!