I don’t know if distributed systems is consider part of “Computer Science” but it is a much more common problem that I see needs to be solved.
I try to write systems in the simplest way possible and then use observability tools to figure out where the design is deficient and then maybe I will pull out a data structure or some other “computer sciency” thing to solve that problem. It turns out that big O notation and runtime complexity doesn’t matter the majority of the time and you can solve most problems with arrays and fast CPUs. And even when you have runtime problems you should profile the program to find the hot spots.
What computer science doesn’t teach you is how memory caching works in CPUs. Your fancy graph algorithm may have good runtime complexity but it completely hoses the CPU cache and you may have been able to go faster with an array with good cache usage.
The much more common problems I have is how to deal with fault tolerance, correctness in distributed locks and queues, and system scalability.
Maybe I am just biased because I have a computer/electrical engineering background.