For me the most useful skill has been to recognise when I'm doing something that's O(n^2) or worse, especially if it involves doing anything besides just math (e.g. database queries, file reads, web requests, etc) If something is O(n^2) or worse it's a good sign I should probably google around for a better algorithm.

Thankfully python has a rich set of built in datastructures, using a dict (or a hash map in other languages) turns a lot of O(n) problems into O(1) problems. The bisect module turns O(n) problems into O(n log n) problems. I'm always keeping my eye out for more of these big-o-reducers.

That said, in production software it hardly ever matters these days as long as you're not doing anything exceedingly daft. Fast enough is fast enough.