Azure Data Engineer Masterclass
Master enterprise cloud data engineering on Microsoft Azure — building automated ADF pipelines, Databricks PySpark transformations, and Snowflake data lakehouses from scratch.
Course Overview
This comprehensive 3-month program covers end-to-end Azure Data Engineering from foundational SQL and Python up to enterprise data lakehouse architecture. You will learn to build automated ingestion pipelines in Azure Data Factory, process large datasets using Apache Spark on Azure Databricks, and model data for reporting in Synapse and Snowflake.
Quick Facts
Who Should Join
Target Audience
- Software developers and SQL developers transitioning to Cloud Data Engineering
- ETL developers moving from on-premise SSIS/Informatica to Azure Cloud
- Fresh graduates and IT professionals seeking job-ready cloud data skills
Expected Baseline Knowledge
- Basic understanding of SQL queries (SELECT, JOIN, GROUP BY)
- Fundamental knowledge of any programming language (Python or C# helpful but not mandatory)
- Computer with stable internet connection for cloud lab access
What You Will Learn
Curriculum Modules
4 ModulesEach module combines theoretical concepts, practical coding exercises, and milestone assessments.
Hands-on Student Projects
Clearly structured practice exercises and end-to-end simulated capstone projects.
Practice Project: Multi-Source Retail Sales Ingestion
Problem Addressed: Daily sales records arrive in different formats (CSV, JSON) across multiple vendor servers.
An automated ADF pipeline that collects, formats, and stores files into ADLS Gen2 with email alerts.
- Configured ADF pipeline JSON
- Data ingestion verification log
Simulated Business Project: Enterprise E-Commerce Data Lakehouse
Problem Addressed: An e-commerce business needs to aggregate order transactions, customer clickstreams, and warehouse stock into a unified analytics data lakehouse.
A complete Medallion Architecture data lakehouse processing raw clickstreams through PySpark on Databricks into Snowflake reporting tables.
- Databricks PySpark PyBook code
- Snowflake data model scripts
- Power BI dashboard connection
Class Experience & Learning Environment
Live Sessions
Interactive weekend/weekday live sessions with real-time screen sharing and hands-on coding.
Recordings & Access
Full high-definition video recordings uploaded within 4 hours of class for lifelong access.
Assignments & Work
Practical hands-on lab exercises assigned after every module with code review feedback.
Doubt & Support
Dedicated Slack/WhatsApp technical support channels with response within 2 hours.
Lead Industry Trainer
Srinivas Rao
Principal Cloud Data Architect
12+ Years Experience in Enterprise Data Engineering (Azure, Databricks, Snowflake)
Schedule & Transparent Fees
Upcoming Batch Starts First Monday of Next Month
Weekend Batch: Sat & Sun 10:00 AM - 12:30 PM | Weekday Batch: Mon-Thu 8:00 PM - 9:30 PM
Transparent course fee with flexible 2-installment payment plan option
Full refund available if cancelled before the start of the 2nd live class.
360° Career Assistance Scope
Substantiated referral assistance and technical preparation without misleading promises.
One-on-one ATS-optimized resume building session tailored for Cloud Data Engineer roles.
2 Technical mock interviews with detailed feedback on PySpark, ADF, and SQL questions.
Repository of top 150+ Azure Data Engineer interview questions and scenario answers.
Direct referrals to hiring partners upon successful completion of capstone project and mock clearance.
Support Duration: Career placement assistance provided for up to 6 months post-course completion.
- Maintain 80%+ attendance
- Complete all module assignments & capstone project
- Pass technical mock interview evaluation