The Skill That Gets Data Engineers Hired in 2025

Want to land your next data engineering role? Mastering PySpark in Databricks is the career skill that separates interview winners from everyone else. In this video, I’ll show you exactly how PySpark works, why companies rely on it for big data, and how you can use it to stand out in interviews.

What you’ll learn in this video:

🔹 PySpark fundamentals in under 60 seconds

🔹 Why Databricks + PySpark matters for real companies

🔹 Five interview-ready PySpark coding examples (with common mistakes)

🔹 Practical exercise to test your skills in Databricks

🔹 Key interview questions and answers you’ll be asked about PySpark

By the end, you’ll know how to run circles around Pandas, prove you can scale data pipelines, and walk into your next interview with confidence.

👉 Don’t miss the bonus section on clustering vs. partitioning... a mistake even seasoned engineers make. Understanding liquid clustering will level up your Databricks game and help you operate at a senior level.

Fundamentals of Data Engineering (book) https://amzn.to/3IBJFB5
Coursera: Big Data with PySpark https://imp.i384100.net/Vx5LJk
Download the practice files - https://www.gambilldataengineering.co...

Affiliate Disclosure: Some of the links above are affiliate links. This means if you choose to make a purchase, I may earn a small commission at no additional cost to you. These commissions help support the channel and allow me to keep creating free resources for the data engineering community.

Chapters:
00:00 - Introduction & Why PySpark Matters
00:59 - Spark Fundamentals Explained
01:47 - Example 1: Reading Parquet Files in Databricks
02:53 - Example 2: Transformations, Filters & Lazy Evaluation
04:13 - Example 3: Joins & Aggregations at Scale
04:59 - Example 4: Window Functions for Interviews
05:47 - Example 5: Writing to Delta with Partitioning
06:29 - Bonus: Partitioning vs. Clustering
07:01 - Practical Exercise & Interview Questions
08:08 - Resources & Next Steps