Believe me, there's a lot of plumbing moving stuff from point A to B and dealing with poop ("dirty data" is the industry euphemism) in the data engineering and data analyst space.

In my more analytic moments I try to convince myself that data engineering and analysis is like chemical refining, creating useful byproducts out of raw liquids, but in my cynical moments, the plumbing metaphors for it are just so much more evocative.

Still, somehow, I think it is where it all started in the 1950s. "I have all these numbers, I need a machine to help me do something useful".

And then after this came a huge industry with programmers.

For me it is more like back-to-basics.