End-to-End Azure Data Engineering Project | Build a Complete Data Pipeline from Scratch

🚀 Build an End-to-End Azure Data Engineering Project from Scratch! In this hands-on tutorial, we’ll build a real-world data pipeline using Azure Data Factory, Azure Data Lake Storage Gen2, Azure Databricks, and PySpark. We’ll work with a retail business scenario involving five datasets: Categories, Products, Sales, Stores, and Warranty. You’ll learn how Data Engineers ingest, store, clean, and transform data using Azure cloud services. 📌 What You’ll Learn ✅ Design a real-world Azure Data Engineering architecture ✅ Create and configure Azure resources ✅ Build dynamic ingestion pipelines using ADF (Lookup, ForEach, Copy Activity) ✅ Implement Bronze and Silver layers ✅ Connect Azure Databricks securely to ADLS Gen2 ✅ Read and transform data using PySpark ✅ Handle duplicates, null values, and data type conversions ✅ Perform joins and data enrichment ✅ Store transformed data in Parquet format 🎯 Who Is This For? Beginners, aspiring Data Engineers, developers transitioning into Data Engineering, and anyone preparing for Azure Data Engineer interviews. 💻 Technologies: Azure Data Factory | Azure Databricks | ADLS Gen2 | PySpark | Python | Microsoft Entra ID 📂 GitHub: https://github.com/anarwade149/Azure-... ⏱️ VIDEO CHAPTERS 00:00 Introduction 00:27 What Does a Data Engineer Do? 02:23 Real-World Business Scenario 04:37 Azure Data Engineering Architecture 10:26 Creating Azure Resources 14:00 Azure Data Lake Storage Gen2 Setup 17:40 Azure Data Factory Setup 20:40 Building Dynamic ADF Pipelines 49:25 Azure Databricks Setup 01:00:33 Connecting Databricks to ADLS Gen2 01:11:00 Reading Data Using PySpark 01:24:00 Bronze to Silver Transformations 01:42:00 Project Summary 👍 If you find this tutorial helpful, like, subscribe, and share! #azuredataengineering #azuredatafactory #azuredatabricks #pyspark #dataengineering