You will still need data engineers to build the whole data ingestion and processing pipeline (although that can be easy if standardised tools are available, such as spark, it's still a challenge in many cases).
Right, but I'd consider that falling closer to the realm of general software engineering -- similar to tasks of collecting analytics of users or building infrastructure to get data from point A to point B.
Maybe that currently is some parts of the job of an ML engineer. But if that's the only part, I don't think that role should be called one of ML engineer anymore
I am working on solving this problem at the moment - I'm building a product that lets anyone build the ETL pipelines that produce inputs for a ML model. If anyone's interested in beta access (coming month or two) let me know, davedx@gmail.com
