Data Engineering or Databricks interview

Published 2026-09-22 in Data Engineering

If you’re preparing for a Data Engineering or Databricks interview, don’t skip Delta Lake. 💡 Understanding Delta Tables can make a huge difference in how well you explain real-world Lakehouse concepts. I’ve created a Delta Tables — Complete Cheat Sheet covering the concepts I frequently see discussed in Data Engineering and Databricks interviews: 🔹 What is a Delta Table? 🔹 Delta Lake vs Parquet 🔹 _delta_log & Transaction Logs 🔹 INSERT / UPDATE / DELETE operations 🔹 ACID Transactions 🔹 Checkpoints 🔹 Time Travel 🔹 OPTIMIZE & VACUUM 🔹 Schema Evolution & Schema Enforcement 🔹 Delta Table Lifecycle 🔹 Best Practices 🔹 SQL Examples 🔹 Interview Concepts & Real-World Use Cases 💡 The concept to remember: Delta Table = Parquet Files + Transaction Log The transaction log enables Delta Lake to provide capabilities such as ACID transactions, reliable data modifications, time travel, schema management, and scalable data management on top of data lakes. 📌 I created this as a quick revision guide for Data Engineers, especially those preparing for Databricks / PySpark / Lakehouse interviews. If you’re currently preparing for an interview: 👉 Comment below with the Delta Lake question you find most…

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