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Big Tech salaries revealed: How much Apple, Tesla, Amazon, and 10 other tech giants pay their workers, from engineers to salespeople

Big Tech salaries revealed: How much Apple, Tesla, Amazon, and 10 other tech giants pay their workers, from engineers to salespeople

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A Tesla wind tunnel model design engineer gets paid $100,000 a year.

A city general manager at Uber focusing on scooters earns $115,150.

Netflix’s chief marketing officer makes $187,907.

A senior director at Apple gets a cool $340,000.

And a vice president of global affairs and communications at Facebook makes a whopping $655,500.

In ultracompetitive Silicon Valley, tech companies splash out huge sums of cash to attract top talent. But compensation overall remains a closely guarded secret, with firms refusing to disclose their rates as employees take to forums and anonymous social networks to compare pay packets.

But there’s one organization that knows exactly how much tech workers are getting paid: the US government.

When American companies file paperwork for visas on behalf of current or prospective foreign workers, they’re required to say how much compensation the workers are being offered. And every year, the Office of Foreign Labor Certification (OFLC) discloses this salary data in an enormous, enlightening dataset.

Business Insider has analyzed this data to see how some of the biggest and most influential tech companies in the world compare when it comes to compensation — and to inject greater transparency into the hiring process for job-seekers.

The full dataset is huge — featuring tens of thousands of workers and countless different companies. Our analysis focused on 13 key companies: Airbnb, Amazon, Apple, Facebook, Google, Lyft, Microsoft, Netflix, Salesforce, Snap, Tesla, Twitter, and Uber. They span fields from online retail to electric vehicles to social networking, and are collectively some of the most prominent companies working in the technology industry today.

The data is a powerful tool for understanding compensation in the industry. If you’re applying for a certain job, how much should you ask for? If you transfer internally, how might that affect your pay? Are you being underpaid compared to your coworkers?

Comparing salaries across the tech giants

This section explains Business Insider’s methodology for analyzing the dataset. Keep scrolling to view the salary data itself.

Each entry in the underlying dataset includes (among other information) the worker’s proposed salary, as well as their exact job title, and “job type.”

What is job type?

It’s a categorization of each worker into one of hundreds of standardized categories that have been predetermined by the US government. For example, Tesla has five different workers in the dataset with the job type “Chemical Engineer” — but these workers’ actual job titles range from senior cathode engineer to senior test systems engineer and staff research engineer.

These job type categories are the same across different companies, thereby allowing us to fairly compare the companies’ varying levels of worker compensation, even if the exact job titles they use for their workers are different.

The companies employ hundreds of even thousands of immigrant workers in the US (Google submitted paperwork for more than 9,000 prospective foreign workers on applicable visas in 2019, for example), so to make sense of the data and allow for comparisons, Business Insider calculated a set of figures for each job type: The minimum, the 25th percentile, the median, the mean, the 75th percentile, and the maximum.

    The minimum and maximum are exactly what they sound like: The highest or lowest compensation received by a worker with a given job type at a given company. The mean is the average — if you add all the salaries up for a given job type then divide them by the number of data points, you get the mean. If you line all of the salaries for a job type at a company up in order from smallest to largest then pick the one in the middle, that’s the median. And the 25th and 75th percentile are when you line up the salaries from smallest to largest and pick the one that’s one-quarter or three-quarters of the way down, respectively.

Taken together, these figures allow you to see the range and spread that a company pays workers with a certain job type, and how it compares to other companies, without combing through thousands of datapoints one-by-one.

Business Insider has also sorted the varying job types into nine thematic fields — like “Engineering,” or “Scientists” — to make the data easier to navigate.

Select a field and then a job type to compare how different companies pay for similar roles. Not all companies have data for all job types. A single dot means there are not enough salaries in the dataset to show a range for that job type.

Drill down even further into specific companies

Now it’s time to dig deeper.

Looking at job types allows you to make cross-company comparisons, but it groups together workers who aren’t necessarily working the exact same roles. You can find out exactly what different specific roles pay by looking at the job titles themselves.

There are thousands of different job titles in the dataset, corresponding to tens of thousands of workers. So to make the data easier to digest, Business Insider conducted a second analysis on the dataset. This time, workers at companies with the same job titles are grouped together, and for each job title at a company the following figures have been calculated: The minimum, the 25th percentile, the median, the mean, the 75th percentile, and the maximum.

Again, these figures make it easier to absorb the data at a glance — and see the spread of pay for a specific job title.

Select a company, then a field, then a job type, to see the analysis of that job type and then the analysis of all the different job titles that are part of it. Not all companies have data for all job types or titles. A single salary figure means there was not enough data to calculate a range of averages.

The data is illuminating but has limitations

There are caveats and limitations to this data that are important to bear in mind.

First, this data relates to the 2019 fiscal year, from October 2018 to the end of September 2019. Since then, there has been a pandemic and unprecedented economic downturn. Some of the companies analyzed — namely Airbnb and Uber — have announced major layoffs, and some others have slowed hiring. The impact of the crisis on tech industry compensation and offers made to new hires won’t be quantifiable until the full data for FY2020 is available, or perhaps even longer.

Second, this data doesn’t give us full visibility into what a company pays — only what it pays to foreign workers, in roles that it has hired foreign, immigrant workers for. If a company has only hired US citizens for a certain department, then the dataset can’t shed any light on how it pays in that area. Similarly, if a company is accidentally or deliberately underpaying immigrant workers relative to US citizens, the data can’t flag that or adjust for it. (In theory, immigrant workers are paid the “prevailing wage” paid to US citizens.)

The database also does not appear to include equity grants, a core part of compensation packages for many Silicon Valley tech workers. With roles that are heavily dependent on bonuses, like sales jobs, the actual amounts ultimately paid may vary significantly from the figures quoted in the dataset. (An OFLC spokesperson did not respond to requests for clarification on equity and bonuses.)

When it comes to job types, the dataset is reliant on companies deciding for themselves which job type a given worker fits into. Two companies might be hiring two workers for identical positions, but if their lawyers filling out their respective paperwork for the visa applications choose to classify their respective roles as two slightly different job types, this can’t be helped. This is why looking at job-title-level data is so useful for assessing exactly what a company pays for a specific role.

The underlying dataset contained numerous typos in job titles, as well as variations in formatting (e.g. “Sr. Software Engineer,” “Senior Software Engineer,” and “Software Engineer, Senior”). Business Insider attempted to correct these and group the entries that clearly refer to identical roles for the job-title-level analysis, but some variants still remain in the table.

It’s also important to note that not all identical job titles for a given company are grouped together. This is because some people with identical titles nonetheless have different job types, that indicate that they do very different roles. For example, a Microsoft employee whose job title is “Designer” and whose job type is “Graphic Designer” is likely to be doing very different work to another Microsoft “Designer” whose job type is “Computer Hardware Engineer.” Their jobs are likely not analogous, meaning their salaries are not comparable, so they have been kept separate in the table above.

Lastly, entries in the underlying dataset of hundreds of thousands of visa proposals include notes on whether the paperwork it relates to was certified, denied, or withdrawn. Our analysis only included the entries that were accepted, to ensure the data reflects real positions.Credits:Skye Gould: Design DirectorWilliam Stevens: Data Visualization Designer and Developer Aaron Marasco: Principal Engineer, Story CreationFran Lam: Web ProducerAlexei Oreskovic, Michael Goodman: Editors

Explore Silicon Valley compensation in more detail:

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