Knowing the typical time and space complexity for an algorithm (without even understanding one bit about the implementation details) in a given category might be considered too trivial to be even basic, but I submit it's about the most "advanced" piece of knowledge for what a typical engineer really must know to write good, high quality and performant enough code.
Most can get by using a given language's library implementation of an "obvious" data structure and naive algorithms around it. For example, in Python, the "obvious" structure to map keys to values is a dict, and iteration over the keys or item tuples is a typical access pattern. An engineer doesn't need to know whether the dict insert or lookup is amortized O(1) or any other value, and he doesn't need to know the space required is O(n), etc. In almost every case he's likely to put it to use for the dict is fine.
I think we're both saying that it's generally a good level of 1st Principles knowledge for programmers to have.
True. And people who clutter their code by using some fancy "StringStream" class when they could've just used a concatenation are also part of the problem!
Saying that programmers don't need a basic knowledge of algorithms is like saying drivers don't need to know how to back up a trailer or do a 3 point turn. Over 90% of the time, you don't need it. But when you do, you really do!