Data Engineering on Microsoft Azure is a comprehensive, hands-on training program designed to teach you how to design, build, automate, and manage data solutions using Azure’s powerful analytics and storage services. This course provides the essential skills needed to work with modern data architectures in the cloud, preparing you for real-world data engineering workloads across enterprise environments.
You’ll learn how to ingest, transform, store, and serve data using Azure services such as Azure Data Factory, Azure Synapse Analytics, Azure Databricks, Azure Stream Analytics, Azure Data Lake Storage, Event Hubs, and more. The course also covers key concepts in data pipeline orchestration, distributed processing, data governance, security, and cost optimization.
 
Through hands-on labs and practical scenarios, you will gain the technical proficiency needed to build scalable, reliable, and secure data engineering solutions that support analytics, machine learning, and business intelligence on Azure.
 
What You’ll Learn
Core principles of data engineering on the Azure cloud
Designing and building scalable data ingestion pipelines
Transforming and orchestrating data flows with Azure Data Factory
Working with Azure Synapse Analytics for warehousing and analytics
Implementing big data processing using Azure Databricks and Spark
Managing data lakes and hierarchical storage with Azure Data Lake Storage
Streaming data processing using Event Hubs and Stream Analytics
Applying data governance, security, and compliance best practices
Optimizing performance and costs in Azure data architectures
 
Who This Course Is For
Data engineers and analytics professionals
Cloud engineers working with Azure data services
ETL developers and BI engineers transitioning to cloud ecosystems
Students and IT professionals preparing for Azure data engineering roles
Anyone seeking hands-on experience with Azure’s end-to-end data platform