Data scientists and machine learning engineers frequently gather data in order to solve a problem. Because the problem they are attempting to solve is often highly relevant and exists and occurs naturally in this messy world, the data that is meant to represent the problem can also end up being quite messy and unfiltered, and often incomplete.
This is why in the past several years, positions with titles such as Data Engineer have been popping up. These engineers have the unique job of engineering pipelines and architectures designed to handle and transform raw data into something usable by the rest of the company, particularly the data scientists and machine learning engineers. This job is not only as important ...
