Data Engineer Salaries Around The World (2019)

Your potential salary as a data engineer heavily depends on where you are based; but cost of living also varies around the world. Wondering where you can actually earn more? Let's take a closer look at the United States, Europe and Asia to compare and benchmark data engineering salaries.

Data Engineering Salaries in the United States

The average Data Engineering salary in the United States is $116,591 per year (Glassdoor) and the current range-band for the United States is between $71,500 and $192,316 (Ziprecruiter). Netflix is the top-paying company, with an average high of $192,316 per year (Indeed). Experience has a positive effect on salary, as does being based in the Bay Area, with many senior data engineers from San Francisco earning an average salary of $172,603 per year (CIO).

Data Engineering Salaries in the European Union

The average Data Engineering salary in Europe is €61,961 per year and the current range-band for Europe is quite wide, spanning between €31,218 and €105,059. There is a big gap between countries, with Scandinavia & Switzerland ranking the highest, with a range of €85,532 to €105,059; and Italy and Spain as the lowest, with a range of €27,218 to €49,980 (DataCareer/PayScale). Overall experience has a positive effect on salary, with senior data engineers earning an average of €10,000 to €25,000 extra per year depending on country.

Data Engineering Salaries in the Asia Pacific Region

The average Data Engineer salary in Asia is $36,974 per year and the current range-band for Asia is between $11,562 and $76,373 per year. There is a big gap between countries, with Australia & Singapore ranking the highest with a range of $43,473 to $76,373, while India and China are as the lowest, with a range of $11,562 to $16,488.

Comparing the salary range-bands for Data Engineers globally:

Comparing Data Engineer salaries in the Asian Pacific region:

Sources: AUS, CH, IN, SIN

Comparing Data Engineer salaries in the European Union:

Sources: DE, UK, ES, CHF

What It Actually Means: From Burgers to iPhones

Looking at raw numbers for salary means very little until you connect this with the relative purchasing power of each unit of currency. The Big Mac Index is a well-known way of comparing the Purchasing-Power Parity (PPP) of different countries or regions, using a fairly standardized item: a burger. At Data Council, we took this idea a step further and developed the iPhone Index.

Introducing: The iPhone Index by Data Council

The idea behind the iPhone Index is to go beyond burgers to include a highly beloved gadget of most tech-obsessed geeks: their smartphone. For some extra fun we compared the prices of the iPhone XR 64GB across our regions to calculate the PPP of individual regions relative to the data engineering salary in said region.

Comparing the Purchasing-Power Parity (PPP) of Data Engineers in our three regions:

*Not factoring in taxes, healthcare, transportation, pensions and other deductions, etc

As you can see on the chart above, a Europe-based Data Engineer can double the amount of iPhone XRs they can buy compared to their Asia based counterpart - or purchase 651 more Big Macs! A US-based Data Engineer can buy 2 more iPhone XRs than their European counterparts - but 130 fewer Big Macs, which also shows the variations in PPP across goods. 

If you are considering competing job offers in different regions, you should obviously take other factors into account, such as quality of life, and more granular, city-level data – but this post will hopefully have given you a good regional overview.

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