I have experienced the same thing...but I just don't think it has anything to do with whether the positions are labeled data scientist or data engineer.
And I would warn you from my experience teaching statistics to undergraduate engineers...they are not going to be much better. Regularly get 'hey we have this data what test can we run?' 'what are you trying to show?' 'we don't care we just need to run a statistical test' conversations.
To be clear, I totally agree with you. I wasn't just arguing for changing labels, I was arguing that there is one set of "engineering" focused skills (e.g. building data pipelines, data warehouses, tagging events, etc.) and a different set of analysis skills (e.g. machine learning, statistical tests, etc.) and you shouldn't over-index on the latter without having enough of the former.
And I would warn you from my experience teaching statistics to undergraduate engineers...they are not going to be much better. Regularly get 'hey we have this data what test can we run?' 'what are you trying to show?' 'we don't care we just need to run a statistical test' conversations.