Hi Databricks Community,
I wrote an article sharing my thoughts on where data engineering is heading in the AI era.
For a long time, data engineering has been about pipelines, transformations, validations, trusted layers, and dashboards. That foundation will always matter. But I believe the next chapter is about going one level deeper: helping people understand not only what happened, but also why it happened, who is impacted, and what action should be taken next.
In real data projects, the hardest part is often not just moving data. It is explaining the data. A count drops. A field goes missing. A join filters records. A business rule changes. A dashboard shows the signal, but teams still need context to understand the story behind the numbers.
That is where I believe Data + AI can play a powerful role โ not by replacing data engineers, analysts, or BI, but by making data systems more conversational, contextual, and decision-ready.
The future I see is built on trusted data, strong governance, quality checks, lineage, business context, and human judgment.
BI is the foundation.
AI is the next layer.
Human judgment is still the most important part.
Would love to hear thoughts from this community: how do you see Data + AI changing the role of data engineers over the next few years?
Article: https://medium.com/towards-data-engineering/the-next-chapter-of-data-engineering-is-intelligent-deci...
