291–300 of 596 posts
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I have FAANG on my resume and this is definitely not the case lol. Then again, it’s Amazon which most people regard to have the dumbest engineers so…
It really should be FG. Facebook and google pay way better than any of those other companies.
My story (hence the throwaway account)... Last year we got no pay rises and were told "no increases this year because covid uncertainty". This year it's a rather megre 2% percent that doesn't even beat inflation, even more so when viewed over two flat years.
I'm obviously looking around and can likely get some small increase, but I'm not seeing the crazy increases or behaviour this article talks about.
The whole remote work move also seems like it would apply downward pressure to some of the top locations. For example I can now compete for remote jobs based in London and would be quite happy being paid a lot less than a typical local London salary given I live significantly further north where salaries are much lower. And potentially if any US tech firms are open to remote workers from the UK they'll find they can get top quality devs at a fraction of the price. So why is remote work being blamed for driving salaries up, shouldn't it have opened up the talent pool for hiring companies just as much as it's opened up the potential choice for applicants.
It feels like the US job market is so hugely skewed in comparison to the rest of the world that it's slightly insane.
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For those of you who have done this, how do you maximise your compensation? Tips appreciated.
Just to add my own data point. I studied leetcode for 6 months during covid. Sent about 30 applications interviewed at 10 companies and received 8 offers. 2 of these offers where double my current TC through negotiation. It's not just FAANG but startups making very good offers. I have 3 YOE. For negotiation: Always ask for at least 20% more + a signing bonus Have competing offers Interview well Be willing to walk awa…
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1. Look on glassdoor, indeed, whatever site you want to use to find out salary expectations in your role/area 2. When asked, give this number as your desired target, but a lot of times they ask about old pay. if the old pay differs greatly, avoid the topic by pointing out how 'the old job requirements are different, benefits are different, etc. But if they press on this number, tell them, don't lie or completely avoi…
> a lot of times they ask about old pay Been in the industry 25 years and never once agreed to disclose my previous pay. Don’t do it. Ever. It’s none of their business and will only be used against you.
Anyone in the ag-tech sector state side?
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This used to be fairly common actually. Facebook interns got automatic Google onsites for a long time. Not Amazon or Microsoft interns though - apparently we aren’t worthy.
G skipped my phone screen coming from A.
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> What sort of software do you have to be writing besides magic money printing machines for it to be worth that amount of money? My understanding is that you have to get into FAANG or be in certain roles at certain HFT firms. I’m also pretty sure these are TC numbers are large chunks of those numbers are stock options.
Even in FAANG I have a hard time understanding how any developer is worth that amount of money though. I know a solid number of FAANG and ex-FAANG devs -- the stuff they work on (from what I've heard) isn't much different from the sorts of software I assume most people in SaaS startups work on. Outside of scale (which is significant). A lot of it is internal tooling though, which never hits absurd amounts of scale. I…
I work in one of the data platform teams at a social media company. Between our 3 HDFS clusters, we're storing more than an exabyte of data. At our scale, we have to tune our workloads carefully to make sure that problems of scale are not noticeable to internal customers (data scientists, analysts, etc.).
We basically have an entire org of highly paid engineers focused on making sure people can use that data efficiently. So we have a team of people working on storage, on Spark, on Presto/Trino, on data ingestion, and so on.
So my understanding is that we're investing in engineers to improve data science productivity, so that they can do analysis without having to understand the internals of all our systems, so that executives can make informed decisions backed by data to continue printing money. Or something like that...