AZURE DATA ENGINEER COURSE
The Azure Data Engineer Course is designed for learners who want to build expertise in managing, transforming, and securing data on the Microsoft Azure platform. This program covers essential concepts such as Azure Data Factory, Azure Synapse Analytics, Azure Data Lake, Databricks, Power BI, and SQL. You will gain hands-on experience in designing modern data solutions, building ETL pipelines, implementing real-time streaming, and optimizing data storage for analytics. The course also prepares you for the Microsoft Certified: Azure Data Engineer Associate (DP-203) certification, making you industry-ready. With real-time projects and case studies, learners will develop practical skills to manage structured and unstructured data, enabling businesses to make data-driven decisions. Ideal for fresh graduates, IT professionals, and career switchers, this training opens doors to high-demand roles such as Azure Data Engineer, Data Analyst, and Cloud Data Architect across industries.
Course Objectives – Azure Data Engineer
The Azure Data Engineer course is designed to equip learners with the technical expertise required to design, implement, and manage data solutions on Microsoft Azure. The program focuses on building proficiency in Azure Data Factory, Azure Synapse Analytics, Azure Data Lake, Databricks, and Power BI to help professionals handle large-scale data processing and analytics. By the end of this course, learners will be able to create secure, scalable, and optimized data pipelines, integrate structured and unstructured data sources, and transform raw data into meaningful business insights. This training also prepares students for the Microsoft Certified: Azure Data Engineer Associate (DP-203) certification, enhancing career prospects in the cloud and data engineering domain.
Key Objectives:
Understand Azure architecture and data engineering fundamentals
Design and implement scalable ETL pipelines using Azure Data Factory
Work with Azure Data Lake, Synapse, and Databricks for data storage & analytics
Integrate structured, semi-structured, and unstructured data sources
Build data models, reports, and dashboards with Power BI
Implement data security, governance, and monitoring practices
Gain hands-on experience through real-time projects and case studies
Prepare for Microsoft Azure Data Engineer certification (DP-203)
Azure Data Engineer Curriculum
Overview of Microsoft Azure and cloud concepts
Understanding data engineering roles and responsibilities
Azure subscription, resources, and resource groups
Data storage options in Azure (Blob, SQL, Cosmos DB)
Introduction to Azure security and governance
Basics of Azure CLI and portal navigation
Working with Azure SQL Database and Azure Cosmos DB
Designing and implementing data warehouses
Managing structured, semi-structured, and unstructured data
Partitioning, indexing, and performance tuning
Data backup, replication, and disaster recovery strategies
Security features for data storage
Introduction to Azure Data Factory and pipelines
Building ETL/ELT processes for data integration
Working with linked services, datasets, and activities
Data transformation with mapping and wrangling flows
Scheduling and monitoring data pipelines
Integrating ADF with on-premises and cloud sources
Introduction to Azure Synapse and dedicated SQL pools
Loading and querying large datasets
Data modeling and schema design
Optimizing query performance and scalability
Integration with ADF and Power BI
Security and workload management in Synapse
Introduction to Databricks and Apache Spark architecture
Building big data pipelines using Databricks notebooks
Data ingestion, transformation, and advanced analytics
Machine learning workflows with Databricks ML
Integration with Data Lake, Synapse, and ADF
Real-time streaming data processing
Setting up Azure Data Lake Gen2
Storing and managing large-scale datasets
Working with hierarchical namespace
Access control and security policies for ADLS
Integration with ADF, Databricks, and Synapse
Optimizing storage performance and cost
Introduction to Power BI service and desktop
Connecting Power BI with Azure data sources
Building interactive dashboards and reports
DAX queries and data modeling
Row-level security and data governance in Power BI
Publishing and sharing dashboards
Implementing role-based access control (RBAC)
Data encryption and compliance in Azure
Azure Monitor and Log Analytics for data solutions
Data governance with Azure Purview
Best practices for auditing and monitoring
Ensuring data quality and reliability
End-to-end data pipeline project using ADF & Synapse
Big data processing project with Databricks & ADLS
Business intelligence project with Power BI integration
Case studies from retail, finance, and healthcare domains
DP-203 certification exam guidance and mock tests
Resume building and interview preparation
Benefits of Azure Data Engineer Course
The Azure Data Engineer Course provides learners with the expertise to design, build, and manage advanced data solutions on the Microsoft Azure platform. With businesses increasingly adopting cloud-based analytics and big data solutions, skilled Azure Data Engineers are in high demand across industries. This course not only covers Azure Data Factory, Synapse Analytics, Databricks, Data Lake, and Power BI, but also focuses on hands-on real-world projects that make learners job-ready. By preparing for the Microsoft Certified: Azure Data Engineer Associate (DP-203) certification, students can validate their skills and secure opportunities in top organizations. Whether you are a beginner or a professional looking to upskill, this training equips you with practical knowledge to handle end-to-end data engineering workflows, ensuring faster career growth in the cloud data domain.
Key Benefits:
Master Azure’s core data services: ADF, Synapse, Databricks, and ADLS
Gain practical exposure through real-time projects and case studies
Learn to design, build, and optimize secure and scalable data pipelines
Prepare for the DP-203 Azure Data Engineer certification
Enhance career prospects with high-paying job roles in data engineering
Hands-on learning with Power BI for data visualization and reporting
Placement assistance, resume building, and interview preparation
Opportunity to work in industries like finance, healthcare, retail, and IT
Who is Eligible for the Azure Data Engineer Course
The Azure Data Engineer course is designed for both beginners and experienced professionals who want to build expertise in cloud-based data engineering. Since the course covers fundamentals to advanced concepts, learners from IT and non-IT backgrounds can enroll. It is especially valuable for professionals working in data analysis, database management, ETL development, business intelligence, and cloud computing, as well as fresh graduates seeking to start a career in data engineering. With businesses increasingly adopting Azure for big data and analytics, this course is ideal for anyone aspiring to become a Data Engineer, Cloud Engineer, or Data Analyst in top organizations.
Key Eligibility Points:
Fresh graduates from Computer Science, IT, Statistics, or related fields
Software engineers, database administrators, and ETL developers
Data analysts and business intelligence professionals seeking to upskill
Cloud professionals interested in specializing in Azure data solutions
Professionals from non-technical roles (finance, operations, marketing) with strong analytical interest
Anyone preparing for the Microsoft Certified: Azure Data Engineer Associate (DP-203) exam
What You Will Learn in the Azure Data Engineer Course
In the Azure Data Engineer course, you will gain in-depth knowledge of designing and implementing modern data solutions on Microsoft Azure. The program focuses on building expertise in Azure Data Factory, Synapse Analytics, Databricks, Data Lake, SQL, and Power BI to manage structured, semi-structured, and unstructured data. You will learn how to design ETL pipelines, build scalable data storage, integrate multiple data sources, process big data in real-time, and create dashboards for visualization. With hands-on labs and real-time projects, you will develop the technical and analytical skills required to transform raw data into actionable business insights. This training also prepares you for the Microsoft Certified: Azure Data Engineer Associate (DP-203) certification, ensuring career growth in the cloud and data engineering domain.
Key Learning Outcomes:
Master Azure Data Factory for building ETL/ELT pipelines
Work with Azure Synapse Analytics for large-scale data warehousing
Gain hands-on experience with Azure Databricks for big data and ML workflows
Store, secure, and optimize large datasets using Azure Data Lake
Build interactive dashboards and data models with Power BI
Integrate structured and unstructured data sources in real-world projects
Learn to implement data security, governance, and monitoring in Azure
Prepare for Microsoft Azure Data Engineer certification (DP-203)
Job Roles After Completing the Azure Data Engineer Course
Completing the Azure Data Engineer Course opens up diverse and high-demand career opportunities in cloud data engineering, analytics, and big data management. As organizations increasingly adopt Azure for data storage, integration, and analytics, certified professionals are highly valued for building secure, scalable, and optimized data solutions. Learners can pursue roles across industries like IT, finance, healthcare, retail, e-commerce, and consulting, with attractive salary packages and global career prospects.
Key Job Roles You Can Apply For:
Azure Data Engineer – Design and manage Azure-based data pipelines and storage solutions
Data Engineer – Build and optimize data workflows, ETL processes, and big data solutions
Cloud Data Engineer – Implement and manage cloud-native data solutions using Microsoft Azure
ETL Developer – Develop and maintain Extract, Transform, Load (ETL) pipelines for large datasets
Business Intelligence (BI) Developer – Create dashboards, reports, and analytics solutions using Power BI and Synapse
Big Data Engineer – Process and analyze large-scale structured and unstructured datasets
Database Administrator (Azure SQL / Cosmos DB) – Manage and optimize cloud-based databases
Data Analyst (Azure Specialization) – Perform advanced analytics and visualization for business decision-making
Azure Data Engineer Frequently Asked Questions
An Azure Data Engineer designs, builds, and manages data pipelines, integrates multiple data sources, and ensures data is accessible, reliable, and secure on the Microsoft Azure platform
No, prior experience is not mandatory. Fresh graduates and beginners can join. However, knowledge of SQL, databases, or programming (Python/Scala) will be an added advantage.
Basic understanding of databases, data analytics concepts, and cloud fundamentals is helpful, but the course starts from the basics, making it beginner-friendly.
Yes, the training is aligned with the Microsoft Certified: Azure Data Engineer Associate (DP-203) certification, which validates your skills in data engineering.
You will gain hands-on experience with Azure Data Factory, Synapse Analytics, Databricks, Data Lake, Azure SQL, and Power BI.
You can pursue roles like Azure Data Engineer, Data Engineer, Cloud Data Engineer, ETL Developer, BI Developer, and Big Data Engineer with top companies worldwide.
Yes, it is ideal for IT professionals, data analysts, database administrators, and cloud specialists looking to upskill in cloud-based data engineering.
Far far away, behind the word mountains, far from the countries Vokalia and Consonantia, there live the blind texts. Separated they live in Bookmarksgrove right at the coast
The duration typically ranges from 2 to 3 months, depending on the training mode (online/classroom) and the learner’s pace. Fast-track options are also available.
Yes, the course includes real-time projects and case studies on data pipelines, ETL workflows, and analytics dashboards, ensuring practical, job-ready skills.
