Azure Data Engineer Training – Take the Next Step Towards Your Career!
Azure Data Engineer Online Training | Azure Data Engineering Course with Placement Assistance
Build practical, job-oriented data engineering skills with our instructor-led Azure Data Engineer Training program. This course is designed for freshers, graduates, software professionals, database professionals, cloud engineers, ETL developers, BI developers, data analysts, and working professionals who want to build a career in Microsoft Azure Data Engineering.
Our training focuses on practical concepts, hands-on labs, real-time project scenarios, cloud data pipelines, Azure Data Factory, Azure Databricks, Azure Synapse Analytics, SQL, PySpark, Data Lake, Delta Lake, ETL/ELT, interview preparation, and placement assistance.
Whether you are searching for Azure Data Engineer Training, Azure Data Engineer Online Training, Azure Data Engineering Course, or Azure Data Engineer Training with Placement, this program provides a structured learning path from fundamentals to real-world implementation.
Why Join Our Azure Data Engineer Training?
✓ Live, In-Depth Azure Data Engineer Training — learn modern cloud data engineering concepts through live, instructor-led sessions. The course helps you understand how enterprise data is collected, transformed, processed, stored, and analyzed using Microsoft Azure services.
- Azure Fundamentals
- Data Engineering Fundamentals
- SQL
- Python Basics
- Azure Data Factory
- Azure Data Lake Storage
- Azure Databricks
- Apache Spark
- PySpark
- Delta Lake
- Azure Synapse Analytics
- ETL and ELT
- Data Pipelines
- Data Warehousing
- Data Integration
- Data Transformation
- Performance Optimization
- Security
- Monitoring
- Real-Time Project Scenarios
Azure Data Engineer Online Training
Our Azure Data Engineer Online Training provides live instructor interaction and practical cloud-based learning without requiring classroom attendance. Students can attend online sessions from Hyderabad, Bangalore, Chennai, Pune, Mumbai, Delhi, USA, UK, Canada, and other locations.
- Live instructor-led classes
- Practical hands-on sessions
- Real-time project scenarios
- Cloud data engineering concepts
- Recorded session access
- Study materials
- Assignments
- Interview preparation
- Resume preparation
- LinkedIn profile optimization
- Job application guidance
- Placement assistance
Azure Data Engineering Course – What You Will Learn
Our Azure Data Engineering Course covers the technologies and concepts required to design and implement modern data platforms on Microsoft Azure.
- Ingest data from multiple sources
- Build ETL and ELT pipelines
- Transform structured and unstructured data
- Store large volumes of data
- Process data using Spark
- Design data lakes
- Create data warehouses
- Build scalable data pipelines
- Monitor data workflows
- Optimize performance
- Secure cloud data platforms
Azure Data Engineer Course Curriculum
Module 1: Data Engineering Fundamentals
- What is Data Engineering?
- Roles and responsibilities
- Data pipelines
- ETL vs ELT
- Structured / semi-structured / unstructured data
- Batch & stream processing
- Data lakes, warehouses, Lakehouse
- Cloud data platforms
Module 2: Microsoft Azure Fundamentals
- Azure architecture
- Azure regions
- Resource Groups
- Subscriptions
- Azure Portal
- Storage Accounts
- Identity and Access concepts
- Azure Resource Manager
Module 3: SQL for Azure Data Engineers
- SQL fundamentals & SELECT
- WHERE conditions and JOINs
- GROUP BY & aggregate functions
- Subqueries and CTEs
- Window functions
- Stored procedures, views, indexes
- Query optimization concepts
Module 4: Python for Data Engineering
- Variables and data types
- Lists, tuples, dictionaries
- Functions, loops, conditions
- File handling
- Exception handling
- Python libraries
- Data processing basics
Module 5: Azure Data Factory
- Data Factory architecture
- Pipelines, activities, datasets
- Linked Services & Integration Runtime
- Copy Activity and Data Flows
- Parameters, variables, triggers
- Debugging, monitoring, error handling
- Incremental & metadata-driven pipelines
Module 6: Azure Data Lake Storage
- Data Lake concepts & architecture
- Storage accounts and containers
- File systems and folder structures
- Data organization
- Access control & security
- Data ingestion
- Data lifecycle concepts
Module 7: Azure Databricks
- Databricks workspace
- Clusters, notebooks, jobs
- Libraries
- Spark fundamentals
- DataFrames, transformations, actions
- Data processing
- Databricks workflows
Module 8: Apache Spark
- Spark architecture
- Driver and executors
- Cluster concepts
- RDDs and DataFrames
- Transformations & actions
- Lazy evaluation
- Partitioning and caching
Module 9: PySpark
- PySpark fundamentals
- Creating DataFrames & reading files
- Filtering and selecting
- Grouping and aggregations
- Joins and window functions
- Handling null values
- Writing output & optimization
Module 10: Delta Lake
- Delta tables
- ACID transactions
- Schema enforcement & evolution
- Time travel concepts
- Merge, update, delete
- Data versioning
- Performance optimization
Module 11: Azure Synapse Analytics
- Synapse architecture & workspace
- Dedicated and Serverless SQL
- Data warehousing
- External tables
- Data loading & transformation
- Synapse pipelines & Spark
- Security and performance
Modules 12–14: ETL/ELT, DWH & Pipelines
- ETL and ELT lifecycle
- Fact and dimension tables
- Star & snowflake schema
- Slowly Changing Dimensions
- Surrogate keys, data marts
- Data modeling
- End-to-end pipeline development
Modules 15–16: Incremental Loads & Security
- Full vs incremental load
- Watermarking & CDC concepts
- Parameterized pipelines
- Role-Based Access Control
- Managed identities
- Secrets management
- Encryption & secure connections
Modules 17–18: Monitoring & Optimization
- Pipeline and activity monitoring
- Failure analysis & retries
- Logging
- Databricks job monitoring
- Partitioning & file-size tuning
- Caching and efficient joins
- Delta & query optimization
Real-Time Azure Data Engineering Projects
Project 1: End-to-End Azure Data Pipeline
- Source data ingestion
- Azure Data Factory
- Azure Data Lake
- Databricks + PySpark
- Delta Lake
- Azure Synapse
Project 2: Incremental Loading Pipeline
- Incremental loads
- Watermarking
- Pipeline parameters
- Lookup activities
- Conditional processing
- Scheduling
Project 3: Data Lakehouse Implementation
- Azure Data Lake
- Databricks
- Spark
- PySpark
- Delta Lake
Project 4: Enterprise Data Warehouse
- Data Factory
- Synapse Analytics
- Fact tables
- Dimension tables
- Data transformations
- Data loading
Beginner Learning Roadmap
- SQL Fundamentals
- Python Fundamentals
- Data Engineering Basics
- Microsoft Azure Fundamentals
- Azure Data Lake
- Azure Data Factory
- Azure Databricks & Spark
- PySpark
- Delta Lake
- Azure Synapse Analytics
- Data Warehousing
- Real-Time Projects
- Interview Preparation
- Job Applications
Who Can Learn Azure Data Engineering?
- B.Tech / B.E. / B.Sc / BCA / MCA / M.Tech graduates
- Freshers
- Software Developers
- SQL & Database Developers
- ETL Developers
- BI Developers
- Data Analysts
- Cloud Engineers & Azure Professionals
- Python / Java Developers
- Testing & DevOps professionals
- Working professionals
- Professionals planning a career transition
Career Support & Interview Preparation
- ATS-friendly resume preparation
- Azure Data Engineer resume guidance
- Real-time project descriptions
- LinkedIn & Naukri profile optimization
- ADF, Databricks, PySpark & SQL interview questions
- Synapse, Data Lake & Delta Lake interview questions
- ETL/ELT and pipeline scenario questions
- Mock interview guidance
- Job application assistance
- Placement assistance
Placement assistance provides job-search and career support and should not be interpreted as guaranteed employment.
Enterprise Data Workflow
- Application / Database / Files
- Data Ingestion
- Azure Data Factory
- Azure Data Lake Storage
- Azure Databricks
- PySpark Transformation
- Delta Lake
- Azure Synapse
- Analytics / Reporting
Take the Next Step towards Your Azure Data Engineering Career
Develop practical, project-based Azure Data Engineering expertise through structured instructor-led training with complete career support.
- Live Azure Data Engineer Training
- Hands-On Labs & Cloud Practice
- ADF, Databricks, PySpark, Synapse & Delta Lake
- 4 Real-Time Projects
- Recorded Sessions & Study Materials
- Interview Questions & Preparation
- Resume & Profile Optimization
- Job Application Assistance
- Placement Assistance
Learn Azure. Build Pipelines. Work on Real Projects. Get Interview-Ready.
