Top Data salaries at FAANG companies in 2022

It is difficult to discuss salary. Is it?

It’s important to know the pay scale of a position before applying. It prevents candidates from wasting time on opportunities that don’t pay as much as they desire. It also reveals pay gaps between different groups and between genders. Lastly, employees can see if they are underpaid in their current position.

The topic of salary transparency is a timely one. Last week, the UK Government launched a pilot in this area. “A number of companies will run trials aimed at eliminating the gender pay gap by publishing pay rates on all job ads”— Equal Pay Pilot.

Several initiatives have begun where employees discover ways to assess pay within their organizations. You don’t always need the government for that. The Open Salary Initiative 2022 is one instance where HelloFresh employees have participated in revealing their salaries to their colleagues. This is a great “give some, get some” incentive that allows employees to stay anonymous.

Working at Google and knowing many people at FAANG companies (Facebook, Apple, Amazon, Netflix, and Google) inspired me to try and shed some light on data compensation by using data. This is where I began by looking at more than 4,000 data points from sources such as levels.fyi and otta.com to estimate pay.

 It’s time to get started

The median data compensation in 2022 in the US is $187,000. Compensation differs greatly from company to company and from seniority to seniority. For example, the median compensation at Netflix is $450,001.

All you have to do is move to the US, work for Netflix, and get rich.

Particularly if you’re among the fortunate 440 data workers at Netflix, US-based data jobs are lucrative. If you’ve read Reid Hastings’ No Rules Rule book, you know this isn’t by chance. Netflix has a policy where they encourage their employees to seek out other job opportunities and report back on what they receive. If Netflix sees that they’re being outbid, they’ll increase their employees’ salaries and that of their colleagues in similar positions.

 “It costs a lot more to lose people and to recruit replacements than to overpay a little in the first place”— Reid Hastings,No Rules Rule.  In addition to Netflix, the other leading technology firms also have a large number of people in data positions earning over $450,000 total compensation per year.

Data salaries in the US, Europe, and elsewhere

Do you want to know how much US tech and data salaries compare to Europe and the rest of the world? The median US data salary for firms I checked out was $187,000, contrasted with $108,000 in Europe and $87,000 elsewhere. There is no small gap. I was not able to gather as many salary data points outside the US, but the trend is still obvious; you get paid much more in the US. In spite of this, there are plenty of jobs on otta.com that pay more than the UK’s median salary, as seen in the chart.

Data salaries by seniority

The largest tech companies have different levels (L) systems that show seniority. Most employees fall in the range L2-3 (junior or mid) to L6 (expert or manager) but Google has a level all the way up to L10. Those lucky few here will not divulge their wages (a look at levels.fyi reveals that the few reported wages at L8 are over $1 million, so I dare you to dream of what it is like at L10).

Some lucky top paid data people earn upwards $700,000 (and some possibly much more). If you go from L3 to L6, you more than double your salary. You’re now thinking to yourself, $400,000+ annually sounds pretty good. Where do you go from here? Senior Data Engineers at Netflix work on experimentation tooling. You must know about experimentation techniques and statistics in order to work well in cross-functional teams.

You could also join Google as a Data Scientist Technical Lead and work with large data sets, applying advanced analytical methods to solve difficult problems. From what I learned at Google, you can climb the corporate ladder (assuming you have a couple of years of experience) by becoming a Business Data Scientist in Ads & Marketing (see listed below).

It depends on whether you should go after these lucrative positions. The aim of this piece, rather, is to raise the question of whether we should be more open about salaries. While salary is a sensitive subject, it makes for an interesting conversation.

Please get in touch with me to provide me your thoughts.