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Databricks Just Changed the Game with LakeFlow — But Is It Too Smart for Its Own Good?

4 min readJun 15, 2025

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Photo by Timothy Dykes on Unsplash

It’s not often that a new tool makes me stop mid-scroll and say, “Wait… this changes everything.”
But that’s exactly what happened when I saw the demo for Databricks LakeFlow.

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As a data engineer who’s spent years wrangling orchestration tools, managing pipeline chaos, debugging failures at 2am, and duct-taping data quality checks, I’ve always wished for a more seamless, intelligent, and resilient workflow engine.

LakeFlow claims to be just that. So I dove in.

🚀 The Promise of LakeFlow: What Got Me Hooked

LakeFlow isn’t just another tool tacked onto Databricks. It’s a reimagination of how pipelines should be built and operated — deeply embedded into the Data Intelligence Platform, and powered by AI at every layer.

Here’s what stood out to me:

1. LakeFlow Jobs = Orchestration That Actually Feels Smart

You can orchestrate anything — ingestion, notebooks, machine learning training, SQL queries, even model deployment — all from a…

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Nnaemezue Obi-Eyisi
Nnaemezue Obi-Eyisi

Written by Nnaemezue Obi-Eyisi

I am passionate about empowering, educating, and encouraging individuals pursuing a career in data engineering. Currently a Senior Data Engineer at Capgemini

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