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I have felt exactly this on regular full stack teams many, many times, so it’s also not just limited to data teams.

IMO a major factor here is that software engineering is both opaque and esoteric - at least with physical engineering, there’s something people can look at and think they understand.

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My theory is that data is worse again because at least if you're making a website you're expected to end up with a website. The process is opaque and esoteric, but the end-product is somewhat tangible.

A lot of data projects are moving and transforming data no-one cares about. They can fail completely silently, a manager can lie and say 'we've successfully built the data platform which is going to enable AI analytics' and it'll be like a misconfigured S3 or something. No-one's checking the end-product or even understands what it's meant to be.

Excellent point… and one I should know. I spent about 6mo as a data eng (only one at the startup) and long after, found out no one ever had a clue what I was talking about in standup. (To be fair, I was self-teaching, and no-one else knew anything so)

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