If you’ve ever been in the market for a Data Engineering job, or you’re alive and on Linkedin, you’ve probably been constantly inundated with job postings and requests pounding on your emails like a constant mountain stream even bubbling down a hill.
If that’s not the case, then head over to the quarterly salary discussion on r/dataengineering and cruise around the comments for an hour or two. One thing that will become clear quickly is that there is a huge range in pay scales, for apparently the same jobs.
One person is making 190K base and another one on the same stack is making 80K, it’s enough to make you pull your hair out. Heck, I get a constant stream of messages for “great opportunities” for a good 50K less than I make at this moment.
What’s the deal?
Sure, there is always going to be some disparity depending on the person who is the Data Engineer, some people simply deliver twice as much as others and are compensated accordingly. Some have over a decade of experience, some only a few.
Straight to the point.
I will tell you what the deal is. It’s the company(s).
The truth is that this sort of pay disparity exists all across the board, not only in Data Engineering, it’s a human phenomenon, and the Data field is no exception. Companies are simply different and act differently towards employees. Sometimes you’re a widget no one cares about, easily replaceable, and sometimes you end up in a place where people are core to what happens, and are paid accordingly.
- Companies that pay well below market value don’t care and probably have bad cultures.
- Companies that pay at or above market value are investing in people and have good cultures.
- Companies that don’t care about data don’t pay well and have crappy infrastructure and tooling.
- Companies that care about data pay well and have great infrastructure and tooling.
A lot of it boils down to two things.
- Does this company care about people generally, or not so much? Do they invest in people or see them as liabilities that are easily replaceable?
- Does this company care about “data” in a real way? Do they invest in their data?
If you’re a Data Engineer you should find a place to work that cares about people and data, the perfect cross-section. This will maximize your earnings. Although we should not complain as a whole as Data Engineers, salaries generally speaking on average or more than enough to live a good life on.
Overall, data engineers can expect to earn between $96,673 and $130,026 on average annually, with higher earnings possible in certain locations and for those with specialized skills and experience. – AI
How to make more money.
Do you want to make more money, are you underpaid? The answer is simple. Find a new job.
Humans don’t like change, many people get stuck and afraid to move on, and this is what keeps them operating in poor cultures where they are treated poorly, overworked, and underpaid. I’m here to tell you data is still the new oil, even more so with the rise of AI.
You can double you income simply by changing jobs every 1.5 years or so.
Nothing will give you a 20-30% pay bump quicker than changing jobs. You can work hard, even at a good company, and only make that sort of increase after working for a decade. Don’t do it.
Data Engineering pays well AT GOOD Companies. Go get paid.
