How do data roles overlap in your Databricks projects?

juanlozadab — Wed, 21 Oct 2026 15:27:54 GMT

The other day, my brother asked me a simple question:

“What does a Data Engineer actually do?”

I started talking about pipelines, databases, and cloud platforms. His face told me that none of it was helping.

So I tried a simpler explanation using a library:

- A Data Architect designs the blueprint: how everything should be organized, connected, governed, and accessed.
- A Data Engineer makes sure the books arrive, are correctly labeled, stored, and available when someone needs them.
- A Data Analyst uses the library to understand what happened and support business decisions.
- A Data Scientist looks for patterns and builds predictions about what may happen next.
- An AI Engineer builds an intelligent librarian that can understand questions, find information, generate answers, and perform tasks.

The analogy worked better, but it also made me think about how unclear these boundaries can become in real projects.

In my experience, most people have a primary role, but the work rarely stays inside that box.

A Data Engineer may contribute to the architecture, investigate a business metric, help with governance, or support an AI use case. In a Databricks project, the same team may be discussing Lakehouse design, building pipelines, validating data in SQL, and helping move an AI application toward production.

I am curious about how other teams organize this:

- Do you have clearly separated roles or broader responsibilities?
- Who owns architecture and governance in your projects?
- Where do Data Engineering and AI Engineering overlap the most?
- Does the division change depending on the size of the team?

I would love to hear how this works in your organization.

Re: How do data roles overlap in your Databricks projects?

larson096vikky — Thu, 22 Oct 2026 06:33:27 GMT

Hello, I think the boundaries between these roles often depend on the size of the team and the complexity of the project. In smaller teams, people naturally take on multiple responsibilities, while larger organizations tend to have more specialized roles.

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How do data roles overlap in your Databricks projects?

Re: How do data roles overlap in your Databricks projects?