[m0zg]

Stock ranges (as well as refresh grants) are also tied to levels you're hired at. "Largely false" my ass. All of this BS applies _only_ to people with weak skill stacks. Committee doesn't even know your "previous" level elsewhere. They know that you've e.g. built this very impressive distributed system here and now and hopefully it made $MM revenue difference (which you'd be smart to quantify and mention). So if you can do it, you'll get rewarded appropriately. If you can't, you won't. And sure, you can't go E5 to E7, there's just no way. But getting from E5 to E7 (or T5 to T7 at Google) is doable in two promo cycles for someone who's in the right place at the right time, and has the right skill stack. Or in fact in the immediate if they are willing to move to another FANG company.

[nostrademons]

Distributed system & big data knowledge is table stakes for Google engineers. At L4 you will be expected to deal with large distributed systems handling petabytes of data. You probably don't need it for L3 (which includes new grads who would never have had an opportunity to develop that skillset elsewhere), but by the time you're at L4 you should be dealing with that regularly.

This is one of the perks for moving from FAANG to non-FAANG; hiring managers elsewhere know that simply by being an engineer there you will have had exposure to distributed systems and big data, and so bring a transferrable skillset to their company.

I thought about whether your comment is true in the context of Speech & Image recognition and other AI technologies. The Speech leads do seem to have an awfully high number of Distinguished/Fellow engineers (this is the top of the eng ladder, where you can basically write your own ticket and your comp package is enough to retire on). However, there are still an awful lot of L4 engineers working on Speech, many training deep-learning models as part of their daily duties.

FB may be different.

[m0zg]

> Distributed system & big data knowledge is table stakes for Google engineers

True, but observe that knowledge is very different from _experience_. In anything sufficiently complicated there's tons of stuff you won't find in books, and even if you do, you won't pay sufficient attention to. E.g. you could sorta know how a database works (from a university course or something), but if you haven't implemented e.g. a state of the art query engine or a storage manager, you'll still be SOL in practice until you write one or more of those things and actually gain experience.

Knowledge by itself is darn near worthless, it only becomes valuable with experience, particularly if it's in 2 or more related fields.