There are two broad mandates that data teams tend to get formed with: 1) provide data to the company, 2) provide insights to the company. These might sound similar — and they’re certainly both important — but they necessitate completely different skillsets. In fact, I’m going to argue that the conflation of these two objectives is exactly what kills good data talent and confounds the hiring process.
This post is an excellent discussion around an important point: should data teams be engaged in helping business units answer specific questions or do they exist to make data available and facilitate self-service?
There is no consensus on this topic right now. My sense is that modern data teams lean towards enabling self-service ("data as product") because that approach tends to scale better as an organization grows. This approach does, however, rely on business units having strong analytical skillsets of their own.
This article advocates that maturing data teams should skew towards data-as-a-service. I'm not sure that I agree with this perspective but more importantly I think the answer is largely contextual to the particular organization. What's definitely true is that you need to be intentional about designing the interaction paradigm between your data team and the rest of your org and align your hiring decisions with it.