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[2025 EDITION] Azure Data Engineer Interview Questions - with PYSPARK

32.7K views· 757 likes· 152:30· May 25, 2025

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Azure Data Engineer Interview Questions | Azure Data Factory | PySpark | Big 🔍 What You'll Learn: This 3+ hour video will help you crack data engineering interviews by walking you through real-time scenarios. It covers Azure Data Factory, Azure Synapse Analytics, PySpark, Databricks, Azure Data Lake, Azure Key Vault, and big data processing using Spark clusters. Timestamps: 0:00 Introduction 06:00 Azure Free Account 11:11 Azure Resources 19:31 Scenario-1: On-Prem To Azure Migration using ADF 33:06 Scenario-2: Data Ingestion From REST API 50:48 Scenario-3: Data Loading To Azure Data Lake using HTTP 1:00:24 Scenario-4: Fault Tolerance in Azure Data Factory 1:06:34 Scenario-5: Monitoring Alerts in Azure Data Factory Pipelines 1:14:34 Scenario-6: PySpark 1:21:59 Scenario-7: Azure Key Vaults with Azure Data Factory 1:35:55 Scenario-8: Triggers in Azure 1:44:33 Scenario-9: Polybase in Azure 1:47:51 Scenario-10: Azure Data Factory System Design 1:57:48 Scenario-11: AQE in PySpark 2:00:46 Scenario-12: Dynamic Sinks with ForEach and Switch Activities 2:13:19 Scenarios-13: Dynamic Mapping in Azure Data Factory ETL Pipelines 2:21:40 PySpark Memory Management WATCH MY PREVIOUS VIDEOS ➡️Azure End To End Data Project https://youtu.be/uc-u_juRg-w?si=sO_CavjnhNaSnZri ➡️Databricks Tutorial https://youtu.be/7pee6_Sq3VY?si=pPBrTnE2R8PhhHu5 ➡️PySpark Full Course https://youtu.be/94w6hPk7nkM?si=i3u_8ZWkGf6fiGyh REPOSITORY ➡️GitHub https://github.com/anshlambagit/AzureInterviewQuestions ======================================= Join this channel to SUPPORT MY HARDWORK: https://www.youtube.com/channel/UCu7lQE-L5gzt8aD7zuuufjw/join ======================================= Connect with ME LinkedIn - https://www.linkedin.com/in/ansh-lamba-793681184/ Telegram - https://t.me/anshlambadatafam ========================= For COLLABORATION 👇 anshlambacollab@gmail.com ========================= ⭐Hashtags⭐ #azure #dataengineering #bigdata #databricks

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