Data Engineering – Azure Course Overview
Build a Job-Ready Career in Data Engineering with Microsoft Azure
Our Data Engineering – Azure course is designed to help learners
understand how modern organizations collect, process, transform,
store and analyse large volumes of data using Microsoft Azure.
You will gain practical knowledge of Python, SQL, Azure cloud
services, ETL and ELT pipelines, data lakes, data warehouses,
Apache Spark, PySpark and modern Azure data platforms.
The course focuses on hands-on learning and real-world scenarios.
You will learn how Azure Data Factory, Azure Data Lake Storage,
Azure Synapse Analytics and Azure Databricks work together to
build scalable and reliable data engineering solutions.
What You Will Learn
Develop practical skills required to design, build, automate
and maintain modern Azure-based data engineering solutions.
Python Programming for Data Engineering
Advanced SQL & Database Concepts
Microsoft Azure Cloud Fundamentals
Azure Data Lake Storage Gen2
Azure Data Factory
ETL & ELT Pipeline Development
Azure Synapse Analytics
Azure Databricks
Apache Spark & PySpark
Azure SQL Database
Data Lake & Data Warehouse Architecture
Real-World Azure Data Projects
Data Engineering – Azure Course Syllabus
10 Modules
80 Hours Total
12 Projects
-
Introduction to Data Engineering and Data Engineer Roles
1 hr
-
Data Engineering Lifecycle and Modern Data Architecture
1 hr
-
Structured, Semi-Structured and Unstructured Data
1 hr
-
OLTP vs OLAP Systems
1.5 hrs
-
Data Pipelines, ETL and ELT Concepts
1.5 hrs
-
Project: Design a Modern Data Engineering Architecture
2 hrs
-
Python Fundamentals for Data Engineering
1 hr
-
Functions, Modules and Exception Handling
1 hr
-
File Handling and Data Processing
1 hr
-
Working with CSV, JSON and Parquet
1.5 hrs
-
Python Libraries for Data Engineering
1.5 hrs
-
Project: Build a Python Data Processing Pipeline
2 hrs
-
Relational Database Concepts
1 hr
-
SELECT, Filtering, Sorting and Aggregation
1 hr
-
GROUP BY and HAVING
1 hr
-
JOINs, Subqueries and CTEs
1.5 hrs
-
Window Functions
1.5 hrs
-
Project: Build a Business Analytics Database
2 hrs
-
Introduction to Microsoft Azure
1 hr
-
Azure Regions, Subscriptions and Resource Groups
1 hr
-
Azure Resource Manager
1 hr
-
Microsoft Entra ID and Access Management
1.5 hrs
-
Azure Security, Monitoring and Cost Management
1.5 hrs
-
Project: Configure a Secure Azure Environment
2 hrs
-
Introduction to Azure Data Lake Storage
1 hr
-
Storage Accounts and Containers
1 hr
-
Azure Blob Storage and Data Organisation
1 hr
-
Hierarchical Namespace and Access Control
1.5 hrs
-
Data Lake Architecture and File Formats
1.5 hrs
-
Project: Build an Azure Data Lake
2 hrs
-
Introduction to Azure Data Factory
1 hr
-
Linked Services and Datasets
1.5 hrs
-
Pipelines and Activities
1 hr
-
Copy Data and Data Integration
2 hrs
-
Triggers, Parameters and Pipeline Monitoring
1.5 hrs
-
Project: Build an Automated Azure ETL Pipeline
2 hrs
-
Introduction to Azure Synapse Analytics
1 hr
-
Synapse Workspace and Architecture
1.5 hrs
-
Dedicated and Serverless SQL Pools
1 hr
-
Querying Data Lake Data using SQL
1.5 hrs
-
Project: Build a Modern Azure Analytics Solution
2 hrs
-
Introduction to Azure Databricks
1 hr
-
Databricks Workspace and Clusters
1.5 hrs
-
Apache Spark Architecture
1.5 hrs
-
DataFrames and Spark Transformations
1.5 hrs
-
PySpark Data Processing
1.5 hrs
-
Project: Build a PySpark Data Engineering Pipeline
2 hrs
-
Azure SQL Database Fundamentals
1 hr
-
Database Design and Data Modelling
1.5 hrs
-
Data Warehouse Architecture
1.5 hrs
-
Analytical SQL Queries and Optimisation
2 hrs
-
Project: Build an Azure Cloud Data Warehouse
2 hrs
-
End-to-End Azure Data Engineering Architecture
1 hr
-
Data Ingestion and Validation
1 hr
-
ETL Pipeline Development
1.5 hrs
-
Data Lake & Warehouse Integration
1 hr
-
Monitoring, Deployment and Optimisation
1 hr
-
Interview Preparation & Mock Interviews
1.5 hrs
Who Should Attend
This course is suitable for students, graduates, working
professionals and career switchers who want to build practical
skills in Microsoft Azure and Data Engineering.
Freshers & Students
Graduates and students looking to start their careers
in Data Engineering, Cloud Computing and Azure.
Career Switchers
Professionals looking to transition into Data Engineering,
Azure Cloud and modern data platform roles.
Data Professionals
SQL developers, data analysts and database professionals
who want to build Azure data engineering skills.
Azure Enthusiasts
Learners interested in Azure, data lakes, ETL,
analytics and big data processing.
Tools & Technologies Covered
Work with modern technologies used by cloud-based data
engineering teams.
Azure Data Engineering Certification Path
Build your Azure Cloud and Data Engineering foundation and
prepare for relevant Microsoft certification pathways based
on your skills and career goals.
Course Completion Certificate
Receive the Procode Technologies Data Engineering
certificate after completing the course requirements.
Microsoft Azure Foundation
Strengthen your knowledge of Azure cloud services,
identity, security, storage and core cloud concepts.
Azure Data Engineering Certification Preparation
Prepare for relevant Microsoft Azure data engineering
certification pathways covering data ingestion,
transformation, storage, analytics and data pipelines.
Cloud Data Engineering Career
Continue building expertise in Azure data platforms,
analytics, big data and modern cloud architecture.
