Live online · 100 hours · Beginner to Advanced
Azure Data Engineering Course — 10 Weeks across ADF, Databricks, Synapse and Microsoft Fabric
Ten structured weeks from PySpark foundations to production Azure pipelines — ADF, ADLS Gen2, Databricks, Delta Lake, Event Hubs, Airflow and Microsoft Fabric.
What you will be able to do
- Build metadata-driven ADF/Fabric pipelines that scale to hundreds of tables without copy-paste
- Design an ADLS Gen2 medallion lake with Delta and Unity Catalog on Azure Databricks
- Work fluently in Microsoft Fabric: OneLake, Lakehouse, Warehouse, Notebooks, Pipelines, Direct Lake
- Stream with Event Hubs, Kafka-on-Event-Hubs, Stream Analytics and Fabric Real-Time Intelligence
- Govern with Purview/Fabric governance, managed identities, Key Vault and private endpoints
- Pass DP-700 (and understand what carried over from the retired DP-203)
Curriculum — 10 weeks · 50 weekday topics + 10 weekend masterclasses · 5 major projects
Sessions run live; every session is recorded. Labs are hands-on from week one.
- PySpark & Databricks Introduction
- Databricks Date & Common Functions
- Databricks Window Functions
- Data Cleaning with Regular Expressions
- spark-submit Internals
- Weekend lab: Claude Code + Prompt Engineering Special Class
- Spark JSON Processing
- Spark JDBC Processing
- XML, CSV & Pandas Data Processing
- Parquet & ORC
- Delta Lake vs Apache Iceberg
- Weekend lab: Spark File-Format & Performance Lab
- Azure Introduction, Blob Storage & ADLS Gen2
- Azure Data Factory Introduction & Internals
- Core ADF Activities
- Databricks Notebook + Lookup + ForEach
- Parameterization & Mapping Data Flows
- Weekend lab: ADF with Claude Code - JSON-Driven Development
- Schedulers, Key Vault & Triggers
- SCD Type 1, SCD Type 2 & Integration Runtime
- Databricks + ADLS Integration
- Data Governance & Security
- ADF End-to-End Pipeline Project using Databricks
- Weekend lab: ADF Metadata-Driven Pipelines
- Databricks Utilities
- Delta Time Travel & Change Data Feed
- Medallion Architecture on Azure
- Spark Declarative Pipelines (SDP)
- Databricks Optimization
- Weekend lab: Lakehouse Federation + Delta Sharing
- Databricks Asset Bundles (DABs)
- Databricks Lakeflow
- Lakeflow Orchestration Advanced
- Unity Catalog Introduction & Auto CDC
- Unity Catalog Advanced
- Weekend lab: CI/CD with DABs
- Spark Structured Streaming Introduction
- Kafka with Spark
- NiFi + Kafka + Spark Streaming
- Azure Event Hubs Streaming Project
- Structured Streaming, Kafka & Auto Loader Internals
- Weekend lab: Real-Time Azure Streaming Project
- Apache Airflow Introduction
- Airflow Advanced Orchestration
- Testing & Observability
- Performance Tuning Deep Dive
- Spark RDD Internals
- Weekend lab: Production Troubleshooting Workshop
- Microsoft Fabric & OneLake Core Architecture
- Fabric Lakehouse vs Synapse Data Warehouse
- Real-Time Intelligence & Data Activator
- Semantic Models in Microsoft Fabric
- Prepare AI-Ready Analytics Data in Fabric
- Weekend lab: Azure vs Fabric Architecture Workshop
- Claude Code for Data Engineers
- Prompt Engineering
- Codex & GitHub Copilot for Productivity
- GitHub Actions CI/CD
- Interview Tips & Resume Preparation
- Weekend lab: Mock Azure Data Engineer Architecture & Interview Clinic
Hands-on projects
You leave with 5 portfolio projects you can demo in an interview — not toy notebooks.
ADF + Databricks Batch Pipeline
Linked services and datasets, parameterisation, Databricks notebook orchestration and a medallion architecture end to end.
Metadata-Driven ADF Framework
Reusable pipeline design with dynamic expressions, centralised configuration and operational error handling.
Azure Databricks Lakehouse
Incremental ingestion into Delta Lake on ADLS Gen2 with data quality, Unity Catalog governance and optimisation.
Azure Real-Time Streaming
Event Hubs with Kafka compatibility, checkpointing, watermarks and late-data handling.
CI/CD & Production Deployment
Version control, automated tests, environment promotion and deployment governance with Databricks Asset Bundles.
Tools and technologies covered
Who this course is for
- SSIS/Informatica developers moving to Azure
- Data engineers on the Microsoft stack
- Power BI developers going upstream
- DP-700 candidates
Prerequisites
- SQL; basic Python helpful but taught in-course
- Azure free account (₹12,000 / $200 credit) — setup walkthrough in session 1
Frequently asked questions
Microsoft retired the DP-203 Azure Data Engineer Associate exam and DP-700 (Fabric Data Engineer) is the current data engineering certification. We teach the DP-700 objectives as the certification path, and still cover ADF, Databricks and Synapse in depth because that is what production Azure estates actually run on. ~90% confident on retirement specifics — always confirm current status on Microsoft Learn before booking.
Both, and the course covers both. Fabric is where Microsoft-centric BI-driven organisations are heading; Azure Databricks remains the default for heavy engineering and ML workloads. Week 9 ends with an Azure vs Fabric architecture workshop and a decision framework you can defend in an architecture review.
The free account credit covers most labs. Fabric labs use the free Fabric trial capacity. A few Synapse dedicated-pool labs cost a few dollars — we always pause/delete resources at the end of the session.
No, it is built for that transition. Weeks 3 and 4 map SSIS concepts (control flow, data flow, packages, configurations) onto their Azure Data Factory equivalents.
Venu Katragadda or a course advisor will call or WhatsApp you within one working day with the full syllabus, batch dates and fees. For anything urgent, WhatsApp +91-9247159150.
Free download · PDF
Download the full 100-hour syllabus
Every module, every hour, every lab and all three projects — the same document we hand to corporate clients. No email verification loop; the PDF downloads the moment you submit.
- Every week broken down topic by topic with hours
- All 5 portfolio projects in full
- Prerequisites, tools list and certification mapping
- Fees, EMI options, batch timings and the refund policy
What students say about Venu Katragadda
Verified Google reviews from Sreyobhilashi IT students. Read all 320+ reviews →
“Recently took Databricks classes with Venu to upskill in trending technologies, and the experience exceeded all expectations. While I initially sought guidance only on Databricks, Venu provided in-depth training across the entire ecosystem.”
Databricks · Cleared DE Professional Cert · Verified Google review
“This training has exceeded my expectations. Venu explains concepts clearly and uses hands-on examples that make the content easy to understand. I am learning a lot and would definitely recommend.”
Databricks Training · Verified Google review
“I recently completed the Data Engineering course on Databricks and AWS. Venu Sir delivers instruction at the next level, focusing on high-performance learning. He explains every concept clearly and thoroughly, accompanied by practical examples.”
Databricks & AWS Training · Verified Google review
Foundation course or masterclass?
We run two tiers. Most people should start with the foundation course on our sister site and step up later — this page is the advanced one.
Foundation · databrickstraining.in
Azure Data Engineering Training
₹40,000₹25,000
- DP-203 focused of live instruction
- Covers the job-ready core of the stack
- Best if you are new to the platform or changing careers
- Same trainer, same teaching style
Masterclass · this page
Azure Data Engineering Masterclass
₹40,000₹25,000
- 100 hours — roughly 25–30 extra hours of depth
- Internals, performance tuning and cost engineering modules
- Three reviewed portfolio projects instead of guided labs
- Architecture review and certification drill included
- Best if you already work with the stack and want senior-level depth
Not sure which fits? WhatsApp +91-9247159150 and Venu Katragadda will tell you straight — including when the cheaper one is the right answer.
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