If machine learning and data science are your intended domains, does learning data engineering*/architecture help your career prospects or salary? Is knowing both mostly useful for smaller teams/firms where one person wears multiple hats?

*I don't mean doing ETL/data cleaning locally, but on an enterprise scale, on the cloud, etc.

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Yes its always good to understand the data as best as possible. In this case understanding its source and how its ingested.

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For mle almost certainly. For ds, depends on what the expectations are for the ds role since there are many flavors of ds roles / what employers call a ds.

If you're working on pipelines in the ds role then it would help a great deal (very common especially since there are a lot of companies that hire data scientists when they're in need of data engineers first.)

If the role is heavier around product, research, storytelling, visualization, etc. it might still come in handy from time to time but not nearly as much.

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Yeah and at Deloitte IME you can't always trust your team to include people with the right skills, so you're the ultimate backstop, esp at the SC-M levels

Yes. You need to know data engineering. Even in a mature team, you'll likely need to know it to be great at your job.

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Depends how mature your DE counterparts are. I can’t be arsed to learn that stuff so I focus more on keeping them happy

Yes that’s my domain but I got on an engagement where I ended up needing to know data engineering and architecture so I learned it on the fly. I don’t recommend it. The engagement was an analytics engagement and of course now at the end we are doing something completely different so you don’t always know when you’ll need it

Yes, best to know the full value chain of data. To help clients map their gaps and mitigation paths

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