Ultimate Data Engineering Interview Prep in 13 Hours | SQL, Python, Spark & Data Modeling

Описание: Preparing for Data Engineering interviews?

This comprehensive 13-hour course covers the most important topics asked in Data Engineering interviews, from SQL and Data Modeling to Python, Spark, and PySpark. Whether you're a beginner looking to break into data engineering or an experienced professional preparing for your next role, this course is designed to help you build a strong foundation and confidently tackle interviews.

📌 What You'll Learn
✅ SQL Interview Questions & Problem Solving
✅ Window Functions, CTEs, Joins & Query Optimization
✅ Data Modeling Fundamentals
✅ Star Schema & Snowflake Schema
✅ Fact & Dimension Tables
✅ Slowly Changing Dimensions (SCD)
✅ Data Warehousing Concepts
✅ Python for Data Engineers
✅ Spark Fundamentals & Architecture
✅ Transformations vs Actions
✅ Lazy Evaluation & DAGs
✅ PySpark DataFrame API
✅ Joins, Aggregations & Window Functions in PySpark
✅ Performance Optimization Concepts
✅ Real Interview Questions & Follow-up Discussions

Timestamps:
00:00:00 Plan for next 13 hours
00:02:23 Data Engineering Courses
00:03:53 SQL For Data Engineering
03:07:25 Data Modelling and Warehousing
04:56:57 Python For Data Engineering
07:01:30 Spark Fundamentals
08:52:41 PySpark API

Zero to hero(Advance) SQL Aggregation:
   • All About SQL Aggregations | SQL Advance |...  

Most Asked Join Based Interview Question:
   • Most Asked SQL JOIN based Interview Questi...  

Solving 4 Trick SQL problems:
   • Solving 4 Tricky SQL Problems  

Data Analyst Spotify Case Study:
   • Data Analyst Spotify Case Study | SQL Inte...  

Top 10 SQL interview Questions:
   • Top 10 SQL interview Questions and Answers...  

Interview Question based on FULL OUTER JOIN:
   • SQL Interview Question Based on Full Outer...  

Playlist to master SQL :
   • Complex SQL Questions for Interview Prepar...  

Rank, Dense_Rank and Row_Number:
   • RANK, DENSE_RANK, ROW_NUMBER SQL Analytica...  

#sql #python #spark #datamodeling #dataengineering