The issue is that data complexity is also exploding in the age of LLMs, so it still takes a lot of archaeology to get reliable (as opposed to plausible) numbers.

I think this dynamic also requires more data engineers, but I don't personally see the split in demand between those roles that you describe. Data analysts often have business or domain context that data engineers lack.

Perhaps we'll start rolling data analysis work into "operations".