Yep, I am of the opinion that the same issues exist in the data engineering space! I haven’t seen the “full-stack” modifier on many official roles — that one I mostly attribute to people trying to upsell themselves. (I call myself half-stack all the time to poke fun at that naming convention)

However, for the other roles, there has been an evolution within data engineering to a lesser extent — as weird as this sounds, titles seem to be aligned based on the “part of the pipe” with data engineers towards the front of the pipe looking a little more like a back-end engineer and data engineers at the end of the pipe tending to focus on analytics and warehouses — hence for bigger companies, you see “analytics engineers” titles kicking around to represent the difference between that focus.

While probably not as diverse as the “data science” space, data engineers have a broad range of skills and interests. There are many data engineers that have limited exposure to developing upstream infrastructure and there are other data engineers who do not want to curate analytics datasets all day. Though, as you pointed out, at smaller companies regardless of interest or ability, a data engineer is likely to do both.

Thanks for the comment!