If you are truly interested in understanding my point of view -- a great way to do it would be to learn how to use this Clojure DSL: https://github.com/redplanetlabs/specter
You could also think about why Nathan Marz may have bothered to create it.
As for data engineering, I think ChatGPT could tell you a lot, and its training is dated from 2021.
Clojure also has some third party libraries like Specter [1] that make nested traversal and mutation very succinct and performant.
The author of Specter goes so far as to label traversal/update of deep immutable structures as "Clojure's Missing Piece".
I'm still salty about Specter[0] not being ~officially recognised as a necessity when using Clojure.
[0] https://github.com/redplanetlabs/specter
Data driven languages need simple & powerful transformation libraries. `get-in` is repetitive and tiresome to use.
Specter and it's ilk make transformations clear and simple.
No amount of planning or foresight negates the need for data transformation libraries.