Earlier quoted context omitted.
> IRL, this individual is a good but not exceptional engineer having worked with them on a small project. Have you worked with them since they went through this regiment? Doing a DS&A coding problem regiment + system design will change you as an engineer. You might be surprised how good they've become. Also they say they've forgotten. But if they were able to get that position, they probably could do medium level lee…
No home study grind on puzzle problems is a substitute for years of practical experience, which is what most teams actually hope for in their higher-level engineers. The point is not that the friend didn't pick up some implicit knowledge or become a sharper engineer than they were before grinding, it's that by exploiting the screening strategy, they got placed into a job they're not truly qualified for. Are they brig…
But on the other hand, it's also not a very strong signal for my years of experience working on and designing portions of systems. I've never actually done "design a system from scratch", because every system that is big and complex evolved from some smaller and less complex system.
So the kinds of questions that come up in these system design interviews are best answered in real life with "I dunno, I'd pick something simple and refactor it later if it becomes a bottleneck".
"What kind of database would you choose for this?" "Whatever we're already using in production for other things." "How would you model this data?" "As simply as possible, so that we can get it out fast and start learning things."
But these are not interesting answers in these interviews. I have usually found myself saying "well, in real life, I would advocate for simplicity and iteration, but for the purposes of this interview, I'm happy to discuss potential trade-offs in technology selection, architecture, and data modeling".
But I think it's easier to study up on the "right" answers to the architecture and modeling questions, without spending a lot of time learning how to start simple and when to evolve toward complexity, etc.