The theory behind it surely is not a day to day topic, but I think the ability to know the rough time and space complexity of an algorithm you've just written is super important.
I dabbled in CS before ultimately not pursuing it in college. Not every CS concept is critical professionally, but from what I learned at the time, this is a topic that has proven to be a big part of letting me intuit solutions in my day-to-day.
It's definitely important, I just couldn't understand how to do it. But, I will learn it one day :)
It's definitely one of those topics that appears complex and mysterious until you familiarize yourself enough with it to realize that it's basically just a notation for eye-balling the relative growth patterns and performance of comparable algorithms.