Azure Data Engineer Course & Curriculum

NCPL's hands-on Azure Data Engineer training — full curriculum, real projects, certification prep, and job placement support. We train, mentor and place you.

Module 1: Azure Cloud Fundamentals & Data Engineering Basics

Explore Azure cloud platform fundamentals and data engineering concepts.

  • Introduction to Azure Cloud Platform
  • Azure Resource Management and Portal
  • Data Engineering Concepts and Best Practices
  • Azure Data Services Overview
  • Azure Security and Compliance Fundamentals

Module 2: Azure Data Storage Solutions

Master Azure storage services including Blob Storage, Data Lake, and databases.

  • Azure Blob Storage and Data Lake Gen2
  • Azure SQL Database and Managed Instance
  • Azure Cosmos DB for NoSQL
  • Azure Table Storage and Queue Storage
  • Storage Account Configuration and Optimization

Module 3: Azure Data Factory

Build robust ETL/ELT pipelines and data integration workflows.

  • Data Factory Architecture and Components
  • Building ETL/ELT Pipelines
  • Data Integration Patterns
  • Triggers and Pipeline Orchestration
  • Monitoring and Performance Tuning

Module 4: Azure Databricks

Learn Apache Spark on Azure and advanced data processing.

  • Databricks Workspace and Clusters
  • Apache Spark on Azure
  • Delta Lake Architecture
  • Notebook Development and Collaboration
  • Machine Learning Integration

Module 5: Snowflake on Azure

Master Snowflake data warehouse on Azure cloud platform.

  • Snowflake Architecture and Features
  • Data Loading and Unloading
  • Snowflake SQL and Query Optimization
  • Time Travel and Zero-Copy Cloning
  • Integration with Azure Services

Module 6: Azure Synapse Analytics

Explore unified analytics service for big data and data warehousing.

  • Synapse Workspace Architecture
  • Dedicated SQL Pools and Serverless SQL
  • Spark Pools and Notebooks
  • Data Integration with Synapse Pipelines
  • Power BI Integration and Visualization

Module 7: Microsoft Fabric

Discover Microsoft Fabric unified analytics platform.

  • Fabric Platform Overview
  • Data Lakehouse Architecture
  • OneLake Storage and Management
  • Real-time Analytics
  • Data Science and Machine Learning Workflows

Module 8: PySpark and Apache Airflow

Master distributed computing and workflow orchestration.

  • PySpark Programming Fundamentals
  • DataFrame Operations and Transformations
  • Spark SQL and Performance Optimization
  • Apache Airflow Architecture
  • DAG Development and Workflow Orchestration

Module 9: Data Governance, Security & Best Practices

Implement comprehensive data governance and security measures.

  • Azure Purview for Data Governance
  • Data Security and Encryption
  • Access Control and Authentication
  • Data Quality and Validation
  • Cost Optimization and Monitoring