Azure Data Engineering with AI
Microsoft Azure runs the data backbone of half the Fortune 500 — and Azure Data Engineers earn ₹8-15 LPA at entry level. This two-month program walks you through every service you'll touch on the job: Data Factory pipelines, Synapse Analytics, Databricks on Azure, Data Lake Gen2, Stream Analytics, and Cosmos DB. Plus AI integrations via Azure ML and Cognitive Services so you can build the kind of pipelines hiring managers are actually paying for in 2026. Prepares you fully for the DP-203 certification.
0 lessons
What you'll learn
- Design and build production data pipelines on Azure end-to-end
- Implement bronze/silver/gold lakehouse architecture from scratch
- Choose the right Azure service for any data workload + budget
- Tune Spark and Synapse queries to cut compute cost by 60%+
- Implement security and governance with Azure AD + Key Vault + RBAC
- Build streaming pipelines for sub-second analytics with Event Hubs
- Pass Microsoft DP-203 (Azure Data Engineer Associate) certification
- Crack technical interviews for Data Engineer roles paying ₹8-22 LPA
Technologies Taught
Azure Data Factory (ADF) — pipelines, mapping data flows, triggersAzure Synapse Analytics — dedicated + serverless SQL poolsAzure Databricks — PySpark, Delta Lake, MLflowAzure Data Lake Storage Gen2 — bronze/silver/gold tiersAzure SQL Database + Managed InstanceCosmos DB — multi-model NoSQL at planet scaleEvent Hubs + Stream Analytics for real-time pipelinesAzure Key Vault, Active Directory, RBAC for governanceAzure ML + Cognitive Services for AI integrationPower BI Service for the analyst-facing layer
Course Unique Features
- 70+ hours of live, hands-on training on real Azure subscriptions
- Build 4 end-to-end pipelines — from raw ingestion to BI-ready marts
- DP-203 exam preparation included, with mock questions weekly
- Daily 90-minute live class + dedicated doubt-clearing sessions
- Real CDC + slowly-changing dimension implementations
- Cost optimisation patterns most YouTube tutorials skip
- Performance tuning on Synapse + Spark — not just theory
- Direct connection to hiring partners actively interviewing Azure DEs
- Resume + LinkedIn polish + mock technical interviews
- Lifetime access to recordings + Azure project templates
Job Opportunities
Top job positions you can apply for after completing this training.
| Job Role | Experience | Salary Range |
|---|---|---|
| 1. Junior Azure Data Engineer | Fresher to 1 Years | ₹4–6 LPA |
| 2. Azure Data Engineer | Fresher to 3 Years | ₹6–12 LPA |
| 3. Azure Databricks Developer | 2 to 4 Years | ₹8–14 LPA |
| 4. Azure Synapse Analytics Engineer | 3 to 5 Years | ₹10–16 LPA |
| 5. Azure Data & BI Consultant | 4 to 6 Years | ₹12–20 LPA |
| 6. Big Data Engineer (Azure + Spark) | 5 to 7 Years | ₹14–22 LPA |
| 7. Senior Azure Data Engineer | 6 to 8 Years | ₹18–28 LPA |
| 8. Azure Solution Architect (Data Focus) | 8 to 10 Years | ₹25–40 LPA |
| 9. Cloud Data Platform Engineer | 3 to 6 Years | ₹10–18 LPA |
| 10. Azure Data Migration Specialist | 4 to 7 Years | ₹12–22 LPA |
| 11. Cloud Integration Engineer (ADF + Synapse) | 5 to 8 Years | ₹15–25 LPA |
| 12. Enterprise Data Architect (Azure) | 10+ Years | ₹30–50 LPA |
You Can Work As
Azure Data EngineerData Platform EngineerAzure Analytics EngineerSynapse DeveloperDatabricks Engineer (Azure)ETL Developer (Azure stack)Senior Azure DE / Data Architect
Upcoming In-Demand Jobs
AI-Augmented Data EngineerLakehouse ArchitectReal-Time Streaming EngineerMLOps Engineer (Azure)
Course Curriculum
Azure Basics
9 topics
Azure Basics
- •Basics of Cloud
- •Public, Private and Hybrid Cloud
- •IaaS, SaaS, and PaaS
- •Azure Entra
- •Tenant
- •Subscription
- •Management Group
- •Resource Group
- •Azure Portal Overview
Azure Storage Fundamentals
4 topics
Azure Storage Fundamentals
- •Azure Storage Account
- •Azure Blob Storage
- •Azure Data Lake
- •ACL and Permissions
Azure Data Factory Components
9 topics
Azure Data Factory Components
- •Azure Data Factory Overview
- •Integration Run Time
- •Linked Service
- •Pipeline, Dataset and Activity
- •Source and Sink Configuration
- •Copy Data Activity
- •Recursive, Wildcard, File Listing, Mapping, User Properties
- •Parameterization of Copy Data Activity
- •Sequential and Parallel Copy
Data Loading in Azure SQL Server
6 topics
Data Loading in Azure SQL Server
- •Upsert, Pre-Copy Script, and AutoCreate Table Options
- •Handling Multiple Files with Lookup
- •Full Load Pipeline
- •New Watermark and Old watermark Concept
- •Delta Load for Single File
- •Delta Load for Multiple File
Pipeline Monitoring
3 topics
Pipeline Monitoring
- •Monitoring of Activity
- •Monitoring of Pipeline
- •Execute Pipeline Activity
Azure DevOps and Git
5 topics
Azure DevOps and Git
- •Azure DevOps Overview
- •Azure DevOps Integration with ADF
- •Azure Data Factory Integration with Git
- •Git Pull, Git Push
- •Cherry Pick, Git Revert
Azure Key Vault and Security
4 topics
Azure Key Vault and Security
- •Azure Key Vault
- •Managing Keys and Security
- •Azure Key Vault integration with ADF
- •Azure Key Vault Integration with Linked Service
Data Modelling and Design
5 topics
Data Modelling and Design
- •Fact and Dimension Tables
- •Star and Snowflake Schemas
- •SCD Types and Implementation
- •Creating Stored Procedures for Data Modelling
- •Trigger Stored Procedure from ADF
Azure Logic Apps and Notifications
2 topics
Azure Logic Apps and Notifications
- •Azure Logic App
- •Sending Email Alerts using Logic App
Azure Data Factory Advance
5 topics
Azure Data Factory Advance
- •Event-Based, Scheduled, and Tumbling Window Triggers
- •Data flow and Data Transformation Activity
- •If-Else, Metadata, and Web Activities
- •Global Parameter
- •Parameterizing Triggers
Azure Databricks
8 topics
Azure Databricks
- •Overview of Databricks
- •Spark and Spark Architecture
- •Data Lake and Delta Lake
- •Delta Table and Features
- •Processing CSV, JSON AND XML file using PySpark
- •Integration of Azure Key Vault with Databricks
- •Secret Scope and JDBC connector
- •Writing Data to Azure SQL server
Azure Synapse Analytics
6 topics
Azure Synapse Analytics
- •Overview of Azure Synapse
- •Difference between Synapse and Data Factory
- •Synapse Dedicated Pool
- •Synapse Serverless Pool
- •Polybase Copy
- •Synapse Spark Pool
Microsoft Fabric
6 topics
Microsoft Fabric
- •Microsoft Fabric Introduction and Signup process
- •OneLake and Lakehouse in Fabric
- •Synapse Fabric Data Warehouse and Engineering
- •Spark in Fabric and Data Processing
- •Real time Analytics in Fabric
- •Microsoft Fabric with Power BI
Big Data Processing Using Databricks and Spark
20 topics
Big Data Processing Using Databricks and Spark
- •Overview of Databricks and Spark Architecture
- •Databricks Workspace Overview
- •Understanding Databricks Services and Features
- •Cluster Management: Creation, Autoscaling, and Administration
- •RDD (Resilient Distributed Dataset) Overview
- •Data Frame Spark API and Data Source API Fundamentals
- •Conversion between PySpark and Pandas
- •Common Transformation Techniques in PySpark
- •Transformations vs. Actions
- •Usage of Dbutils for File System Interaction
- •Parameterization Techniques in Databricks
- •Table Manipulation with Delta Lake
- •Read and Process CSV, JSON, and XML Files
- •Types of Views in Databricks (Global, Local, Temporary)
- •Managed vs. Unmanaged Tables
- •Versioning and Time Travel in Delta Lake
- •Azure DevOps and Git Workflow Integration
- •Cherry Pick and Git Revert Commands
- •Secret Scope Creation and Management
- •JDBC Connector for SQL Server
Databricks CLI and Backup Process
2 topics
Databricks CLI and Backup Process
- •Databricks CLI Overview and Installation
- •Backup Process Setup for Notebooks and Configurations
Understanding Spark UI
2 topics
Understanding Spark UI
- •Navigating the Spark UI for Job Monitoring
- •Understanding the Stages, Tasks, and Execution Plans
Unity Catalog and SCD (Slowly Changing Dimensions) Implementation
2 topics
Unity Catalog and SCD (Slowly Changing Dimensions) Implementation
- •Overview of Unity Catalog for Data Governance
- •SCD Types (Type 1, Type 2, Type 3) and Implementation
Lakehouse and Medallion Architecture
2 topics
Lakehouse and Medallion Architecture
- •Introduction to Lakehouse Architecture
- •Medallion Architecture (Bronze, Silver, Gold Layers) Overview
Spark Optimization Techniques
5 topics
Spark Optimization Techniques
- •User-Defined Functions (UDF) for Custom Transformations
- •Catalyst Optimizer and Data Frame `.explain` for Optimization
- •Directed Acyclic Graphs (DAG) and Adaptive Query Execution (AQE)
- •Predicate Pushdown and Projection Pushdown
- •Repartition, Coalesce, Cache, and Persist
Handling Complex Data and Advanced Joins
4 topics
Handling Complex Data and Advanced Joins
- •Handling Complex JSON, Struct, and Nested Data Types
- •Data Skew and Techniques for Handling Skewed Data
- •Sort Merge Join, Broadcast Join, and Optimizing Joins
- •Z-Ordering for Efficient Querying
Orchestration and Scheduling Techniques
2 topics
Orchestration and Scheduling Techniques
- •Job Orchestration and Scheduling with Databricks Jobs API
- •Best Practices for Workflow Orchestration
Course content
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Certificate included
On 100% completion
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