Everyone wants to be a data scientist.But no one talks about the data engineer.Utilizing expertise across software engineering, devops, and data science, it’s arguably even more interesting.I analyzed 50 data engineers’ resumes, to see what it takes to get a job.Let’s investigate.
**What job did data engineers hold immediately prior to their first data engineering role?**Most previous roles involved coding. And compared to data science, we see far fewer academic and “mathy” backgrounds.More than 50% of previous roles fell into software engineering (SDE), data science (DS) and business intelligence (BI).
So if you’re interested in data engineering, it may make sense to become a software developer or data scientist first.
**What is the average salary of data engineers?**According to Payscale, the average data engineering role ($92k) pays more than software engineering ($86k) and data science ($87k) roles.We know averages are misleading, but a $6k difference is significant.
I suspect this is partly attributable to data engineer roles being on average more senior than SDE and DS roles. Senior candidates and a small talent pool could drive up the price.That said, you probably shouldn’t move into data engineering (or any role?) just for the money.
**What is the highest education level achieved before obtaining a data engineering role?**Among 50 resumes, 90% had master degrees, 10% had bachelor degrees, and none had PhDs.
The role is arguably less “academic” than data science. So the lack of PhDs doesn’t surprise me, but the high proportion of master degrees does.This could be due to a bad sample, but I suspect there is some rationale behind it.If anyone has incite, I’d love to hear it!
**What major was studied during the highest level of education?**All majors are STEM, and most are CS related.
Compared to data science, there are far fewer economics, business, and math majors.I suspect that previous role is a stronger indicator of suitability than education, but the distribution is still interesting.
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