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"Data engineers don’t understand business." That was the reason a data leader I talked to last year wasn’t looking to hire data engineers and instead wanted to hire data scientists. It truly can be hard to find an individual with both technical and business skills. But I think this points out a larger issue. Those of us that are data engineers can often get stuck in the weeds. We can be so focused on different vendors, performance optimizations, and whether we should be designing a data warehouse vs a data Lakehouse that we miss the point. The business doesn’t really care. Now that’s not to say we should just throw out all the best practices and just deliver something quickly that won’t be reliable or stable. However, we do need to spend time understanding what the business needs, and how we can iterate and deliver MVPs to continuously get them to buy in. They need to see and “feel” so to speak, the outcomes of your work, instead of hearing about how some technical detail is keeping you from delivering the final set of KPIs. They need reassurance. Plus, it helps pinpoint exactly what the business wants, because sometimes they aren’t 100% sure. I believe we can change the mentality of, data engineers who don’t understand business! And to be clear there are plenty of DEs who have amazing business sense!

Benjamin Rogojan gets it. He talks about the tension here, and I think one really good way we as data professionals can make this better is by becoming more business literate ourselves. We can understand basic things like financial statements, which I may even start posting about soon. Then we can both talk to our business colleagues better and deliver better work.

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A few months back I heard a Manager of an analytics team say that "Data engineers don’t understand business." And this was a reason a company wasn’t looking to hire data engineers and instead wanted to hire data scientists. It truly can be hard to find an individual with both technical and business skills. But I think this points out a larger issue. Those of us that are data engineers can often get stuck in the weeds. We can be so focused on different vendors, performance optimizations, and whether we should be designing a data warehouse vs a data Lake house that we miss the point. The business doesn’t really care. Now that’s not to say we should just throw out all the best practices and just deliver something quickly that won’t be reliable or stable. However, we do need to spend time understanding what the business needs, and how we can iterate and deliver MVPs to continuously get them to buy in. They need to see and “feel” so to speak, the outcomes of your work, instead of hearing about how some technical detail is keeping you from delivering the final set of KPIs. They need reassurance. Plus, it helps pinpoint exactly what the business wants, because sometimes they aren’t 100% sure. I believe we can change the mentality of, data engineers who don’t understand business! And to be clear there are plenty of DEs who have amazing business sense! #dataengineering

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Who came first - the data engineer or the data architect? By that I mean, who would you hire first? I saw a great post recently by Eric Gonzalez stating that a data engineer should be the first hire into a new data function. The reason being, partly at least, that architects prefer not to develop, they just design nice stuff. But surely, without some nice designs to work from an engineer won't known what to build? Eric counters this by saying that you'll learn a lot from the initial builds. And then, what about the data model? Or can a good data engineer do all of the above? I know that I am not, and never will be any of the above, so what would you do?

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