Somebody wrote data engineering's obituary before the body was even cold. Weird thing is, nobody told the corpse, which just got a 23% raise and a $125K starting offer.
Every hot take on your feed says AI's coming to eat this job next. Meanwhile the actual hiring numbers are doing the opposite, and the World Economic Forum thinks demand doubles by 2030. So if you're standing outside tech deciding whether this door is worth walking through, you're not choosing between a career and an AI apocalypse. You're choosing whether to trust a LinkedIn eulogy over a paycheck.
Christopher Adan, a senior consulting data engineer with 13 years watching this field mutate through every hype cycle, answers the three questions everyone asks before they start — and the roadmap that keeps you from burning a year on the wrong tool first.
What we get into:
Why data engineer hiring grew 23% in a year everyone insists AI is coming for it
The real difference between a data engineer, a data analyst, and a data scientist — and why only one of them gets blamed when the pipes leak
The exact learning order for SQL, Python, a cloud warehouse, Airflow, and dbt, plus the two beginner projects that prove you can actually build
Which of the three "go deep" skills separates hires from also-rans — and it's not the technical one
The eulogy's still being drafted. Go build something that ruins it.
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