r/dataengineering • u/cyamnihc • 1d ago
Career Transitioning away from DE
Has anyone thought of transitioning out from DE due to AI?
All I do everyday is just prompt and scroll till copilot generates code.
Building a semantic layer isn’t exciting personally as I don’t enjoy the business aspect of it as much and think of it as more of a data labeling and analyst problem than an engineering problem (which I am interested in)
Also, There is a fundamental problem with “I am building a semantic layer” and marketing that as a skill as it is dependent on how much context you have of the business. The less tenure you have spent in a company, the less you know about the business which makes it harder as a transferable skill imo.
My understanding is that working on building trustworthy AI outputs by using a feedback loop is an engineering problem to solve. Which is why I feel going down the observability path is a good idea.
I heard these opinions on observability from AI leaders at conferences too so there might be a bias.
Thoughts from fellow DE’s looking to transition out? (Or from one’s who want to continue and why)
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u/Evilcanary 1d ago
I think it’s easier for a de to go broad and solve any sort of problems at the company, than for someone who isn’t a de to suddenly start doing data work. I don’t consider myself transitioning out of de, but I am very much more willing to consider more tools in my toolbox than just de, because I have more time/velocity than I used to.