Amazon Data Engineering Interview Question Using PySpark |Joins, Group By & Order By

Got an Amazon Data Engineering interview coming up? In this video, I break down one of the Important questions you might face — a real-world problem that tests your mastery of PySpark functions like join, groupBy, and orderBy. I’ll show you step-by-step how to approach it, write clean PySpark code, and think like an Amazon data engineer. You’ll learn how to handle complex data joins, group data smartly, and sort results for deeper insights — exactly the skills Amazon looks for. If you’re preparing for FAANG or any top-tier data engineering role, this video is for you. Don’t just memorize syntax — learn how to apply PySpark to solve real interview questions. Creating the dataframe data = [ (10,20,11,20), (20, 11, 10,99), (10, 11, 20, 1), (30, 12, 20,99), (10, 11, 20, 20), (40, 13, 15, 3), (30, 8, 11, 99) ] schema = "A int , B int , C int , D int" df = spark.createDataFrame(data = data , schema = schema) display(df) 👉 Don’t forget to like, share, and subscribe to Shilpa Data Insights for more real interview prep! Link to Spark playlist: https://www.youtube.com/playlist?list=PLHcpPiCf7ryZf8GAFKcFuYmOxswcCOGz4 Link to Databricks playlist: https://www.youtube.com/playlist?list=PLHcpPiCf7ryZLNLvSsglM05lJXaWngHUH Link to Databricks certification : https://www.youtube.com/playlist?list=PLHcpPiCf7ryZrusmfkgteZvSMO16hagP5 Link to Big data: https://www.youtube.com/playlist?list=PLHcpPiCf7ryYfIrrJBQDa0Vw9BXIY-mUD Link to Interview series for Pyspark: https://www.youtube.com/playlist?list=PLHcpPiCf7ryYp8KKn0sWfLugYEEsF2UOf Need Help ? Connect With me 1:1 -:- https://topmate.io/shilpa_das10 #dataengineering #dataengineer #dataengineeringinterview #pysparkinterview #amazoninterview #shilpadatainsights #bigdata