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At big tech companies, "writing a program over a few hours that is reflective of the kind of work that the company actually does" is not really a good, represen

At big tech companies, "writing a program over a few hours that is reflective of the kind of work that the company actually does" is not really a good, representative performance measure. Often times, you will be solving problems across multiple domains, outside of your area of expertise. You have to take on the role of PM, data scientist, SWE, researcher, etc. Internal restructuring of the company may even take you from working on backend web apis to distributed databases. It is expected that you re-acclimatize and learn quickly. Giving you a take-home test to write some CRUD app isn't necessarily sampling those same attributes. p.s.: also not a fan of classical algorithm style interviews. Clearly, they also have a bias.

ken47 3y ago
> Internal restructuring of the company may even take you from working on backend web apis to distributed databases This is a stretch. It's unlikely that an interview process would test such disparate skills directly, and a competent company will avoid moving an engineer into a role that requires a drastically different skillset without separate verification that they can handle the new role.
stormbeard 3y ago
> Internal restructuring of the company may even take you from working on backend web apis to distributed databases. This isn’t true. I’ve worked in multiple FAANG companies’ infrastructure orgs, including distributed kv stores, as a SWE. Anybody joining those kinds of teams are either specialists, very junior, or already had some kind of experience in the domain before joining. Recruiters that say stuff like “we want strong generalists… blah blah” are not the people who are sourcing candidates for these deep systems roles. It looks a lot like the ML roles.