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Spark DataFrame Mastery

Master PySpark coding — one skill a day, zero Spark infrastructure cost, 30 days to interview-ready.

Course Summary

30-Day PySpark Interview Prep Challenge

This challenge is designed to transform how you walk into a PySpark coding interview.

Most AWS Data Engineering interviews don't test whether you've watched PySpark videos. They test whether you can write PySpark code under pressure.

That's exactly what this challenge prepares you for.

Over 30 days, you'll build your PySpark skills one concept at a time until you can confidently solve real-world coding problems and interview questions.

Why Most People Fail PySpark Interviews

The problem isn't a lack of tutorials.

The problem is a lack of practice.

Most professionals understand PySpark concepts but struggle when asked to write code during an interview.

To make matters worse, practicing PySpark isn't easy:

  • Cloud clusters cost money
  • Local Spark installation can be frustrating
  • Environment setup often takes longer than the actual learning

As a result, many people avoid practicing altogether.

Practice PySpark Without Installing Anything

This challenge removes that obstacle completely.

Every lesson includes a ready-to-use Google Colab notebook.

No installation.
No cluster setup.
No infrastructure costs.

Simply click a button, launch the notebook, connect to your AWS S3 bucket, and start writing PySpark code immediately.

Focus on learning—not setup.

What You'll Learn

Days 1–21: Build Your PySpark Foundation

You'll learn one concept per day, allowing your skills to compound naturally.

Topics include:

  • SparkSession
  • DataFrames
  • Reading and Writing Data
  • Schemas
  • Filtering and Transformations
  • Aggregations
  • GroupBy
  • Joins
  • Window Functions
  • Handling Nulls
  • String Functions
  • Date and Time Functions
  • Spark SQL
  • Performance Best Practices

By Day 21, you'll have the complete PySpark toolkit expected of a Data Engineer.

Days 22–30: Real Interview Practice

The final nine days are focused entirely on interview preparation.

You'll solve realistic coding problems that combine multiple concepts together.

Each problem is solved:

  1. Using SQL
  2. Using PySpark

This mirrors how many AWS Data Engineering interviews are conducted and helps you develop both problem-solving skills and implementation skills.

The challenge concludes with a timed mock interview on Day 30.

Recommended Before You Start (Optional)

To get the most out of this challenge, we recommend completing:

  • PySpark Skill Booster for AWS Data Engineering
  • SQL and RDS Foundations
  • 30-Day SQL Interview Prep Challenge

The PySpark challenge often requires translating SQL logic into PySpark code, so a strong SQL foundation will accelerate your progress significantly.

Your Commitment

This challenge works if you do.

Commit to a finish date.
Put it in writing.
Show up every day.

Thirty days from now, you'll have solved dozens of PySpark problems, built real coding confidence, and be ready to tackle PySpark interview rounds with confidence.

Someone will get that high-paying AWS Data Engineering role.

Make sure it's you.

Course Curriculum

Sachin Chandrashekhar

Lead Data Engineer @ World's #1 Airline

Course Pricing

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