
Explore Azure data engineering by building an end-to-end project suite across 20+ real time projects, featuring Azure Synapse, Microsoft Fabric, data bricks, Azure Data Factory, and a Power BI report.
Set up an adls account in Azure with hierarchical namespace, create a lake house with silver and gold folders, and use pyspark to clean data for a Power BI dashboard.
Build an end-to-end Azure data engineering project: ingest rest API data into ADLS with Azure Data Factory, process with PySpark in Synapse, and publish a daily purchases and revenue report.
Perform schema validation in azure data factory by comparing incoming csv structures against a predefined schema using get metadata and an if condition, ensuring only matching files are processed.
Build an end-to-end retail data pipeline in Microsoft Fabric using medallion architecture (bronze, silver, gold) to clean, unify, and visualize data with PySpark and Power BI.
Deliver an end-to-end Azure data engineering project for retail, using Azure Data Factory, Azure Data Lake Storage, Databricks, medallion bronze-silver-gold, and Power BI visualizations.
Execute an end-to-end Azure Data Factory project to implement SCD type 1, loading daily CSV data from blob storage into Azure SQL Database using upsert, update, and insert operations.
Build an end-to-end Azure Data Factory pipeline using data flow to implement SCD type 2, inserting new records and updating existing ones while tracking historical and current records.
Are you ready to become a job-ready Azure Data Engineer?
This course is your complete, hands-on guide to mastering Azure Data Engineering with 20+ real-time, end-to-end projects across multiple business domains — Retail, Insurance, E-commerce, HR, and more.
We take you from beginner to advanced by covering every major Azure Data Engineering service, including:
Azure Data Factory (ADF) – Build and automate scalable data pipelines
Azure Synapse Analytics – Create and optimize enterprise-scale data warehouses
Azure Databricks with PySpark – Perform advanced big data processing & cleaning
Microsoft Fabric Lakehouse – Store, manage, and analyze data in a unified platform
Fabric Dataflow Gen2 – Implement ELT pipelines with reusable transformations
Power BI – Create stunning dashboards and KPIs directly from Azure data
Medallion Architecture – Organize data into Bronze, Silver, and Gold layers for scalability
What makes this course different?
20+ Real-World Azure Data Engineering Projects — Each project simulates real business scenarios so you can build a professional portfolio
End-to-End Pipelines — From data ingestion to final business dashboards
Multiple Domains — Retail, Insurance, E-commerce, and HR use cases
Advanced Scenarios — Incremental loads, Slowly Changing Dimensions (SCD Type 2), real-time streaming pipelines, data deduplication, and audit-ready solutions
Practical, Hands-On Approach — Learn by doing, not just theory
Career-Oriented Content — Prepare for Azure Data Engineering interviews and DP-203 / Microsoft Fabric certifications
By the end of this course, you will be able to design, build, and deploy enterprise-grade Azure Data Engineering solutions — exactly what top companies are looking for.