PinnedI Almost Got Fired Because of Pandas on Databricks — Here’s What You Should Learn From My MistakeJust because your code works doesn’t mean it scales.May 3A response icon28May 3A response icon28
Databricks Just Changed the Game with LakeFlow — But Is It Too Smart for Its Own Good?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…1d ago1d ago
I Thought Databricks Lakebase Wasn’t Groundbreaking — Then I Took a Closer LookI’ll be honest — when I first saw the announcement for Databricks Lakebase, my reaction was: “Wait… haven’t we seen this before?”3d agoA response icon23d agoA response icon2
So You Want to Become a Data Engineer? Read This First.The hype is real.5d agoA response icon15d agoA response icon1
How I’m Upskilling as a Data Engineer in 2025In 2022, learning Spark and SQL made me feel like a data wizard. In 2025, they feel like table stakes. So what now?Jun 6A response icon5Jun 6A response icon5
Not All Data Errors Throw Exceptions: How Business Logic Violations Quietly Ruin TrustIn today’s world of big data, distributed systems, and real-time analytics, data quality has quietly become the backbone of trustworthy…Jun 5Jun 5
The RAG Pipeline From Hell: How I Survived My Worst Data Engineering WeekThe Costly Mistakes I Made Parsing Unstructured Data for a RAG Project — and How You Can Avoid ThemJun 4A response icon1Jun 4A response icon1
The Data Engineering Interview Pitfalls No One Talks About (But Many Make)“I solved the coding problem. I answered the SQL question. I even mentioned Spark… but I didn’t get the job.”Jun 3A response icon4Jun 3A response icon4
How GitHub Copilot Agent Mode is Reshaping My Workflow as a Data Engineer“Do you want me to just write the test for you?” That’s the kind of nudge GitHub Copilot Agent Mode gave me recently — and it changed how…Jun 1Jun 1
I Had a Colleague Ask Me How to Do Incremental Load on a Complex Reporting Table — Here’s What I…One of the most common performance pain points I see in data pipelines is this:May 29May 29