Data Engineering

★★★★★

(2,095 ratings) 50,000+ Student

Data Engineering on Microsoft Azure - DP 203

Data Engineering on Microsoft Azure refers to the process of designing, implementing, and managing data pipelines and workflows on Microsoft’s cloud platform, Azure. It involves the collection, ingestion, transformation, and storage of data to make it ready for analysis, reporting, or machine learning. Azure’s flexibility and scalability make it a popular choice for organizations looking to harness the power of data in the cloud

Radical Technologies

50,000+ English 40 hours Weekdays / Weekends Classroom / Online / Corporate

Online / Classroom

IT Training Programme

Duration 40 hours

Batch Type Weekdays / Weekends

Mode of Training Classroom / Online / Corporate

Locations Pune, Bangalore, Kochi

Language English

Certification Globally Recognized

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100% placement assistance

What you'll learn

Understand core concepts and architecture from the ground up

Get hands-on with the tools used by working professionals

Build real-world projects you can add to your portfolio

Learn industry best practices and coding standards

Practice with real datasets and real-world scenarios

Prepare for certification and technical interviews

Work on collaborative, team-based exercises

Apply performance tuning and optimization techniques

Understand how the technology fits into a larger ecosystem

Complete assignments reviewed by mentors

Programme Overview

18 sections covering the complete curriculum — a single, progressive learning arc.

40 hours

Training Duration

Core Modules

136

Total Lessons

4.4★

Average Rating

50K+

Students Trained

Foundations & Core Concepts

Get hands-on with the fundamentals and architecture — the building blocks for everything that follows.

Fundamentals Architecture Setup

Hands-On Practical Training

Work through real exercises and assignments designed to mirror what you will do on the job.

Practicals Assignments Labs

Real-World Projects

Apply what you have learned to end-to-end projects that go straight into your portfolio.

Projects Portfolio Case Studies

Advanced Techniques

Go beyond the basics with advanced concepts, integrations and production-grade practices.

Advanced Integration Best Practices

Ecosystem Integration

Understand how this technology connects with the broader tools and platforms used in the industry.

Ecosystem Tools Platforms

Performance & Interview Prep

Master optimization techniques and prepare for the technical interview questions employers actually ask.

Optimization Interview Prep Certification

Who is this programme for?

Whether you're already writing code, working with data, or supporting applications today — this programme is built to take you into a Data Engineering role.

Software Developers

Engineers who want to add this skill set to their toolkit

Analysts & Consultants

Professionals moving into a more technical, hands-on role

IT Professionals

System admins and support engineers upskilling into a new domain

Fresh Graduates

CS/IT graduates aiming for a job-ready technical role

Course Curriculum

18 sections • 136 lessons • 40 hours

Jump to Section

Total Duration

40 hours

100% Practical · Unlimited Doubt Sessions

01 1. Design and Implement Data Storage (40-45%)

Design and Implement Data Storage (40-45%)

02 Design a data storage structure

design an Azure Data Lake solution

recommend file types for storage

recommend file types for analytical queries

design for efficient querying

design for data pruning

design a folder structure that represents the levels of data transformation

design a distribution strategy

design a data archiving solution

03 Design a partition strategy

design a partition strategy for files

design a partition strategy for analytical workloads

design a partition strategy for efficiency/performance

design a partition strategy for Azure Synapse Analytics

identify when partitioning is needed in Azure Data Lake Storage Gen2

04 Design the serving layer

design star schemas

design slowly changing dimensions

design a dimensional hierarchy

design a solution for temporal data

design for incremental loading

design analytical stores

design metastores in Azure Synapse Analytics and Azure Databricks

05 Implement physical data storage structures

implement compression

implement partitioning

implement sharding

implement different table geometries with Azure Synapse Analytics pools

implement data redundancy

implement distributions

implement data archiving

06 Implement logical data structures

build a temporal data solution

build a slowly changing dimension

build a logical folder structure

build external tables

implement file and folder structures for efficient querying and data pruning

07 Implement the serving layer

deliver data in a relational star schema

deliver data in Parquet files

maintain metadata

implement a dimensional hierarchy

08 2. Design and Develop Data Processing (25-30%)

Design and Develop Data Processing (25-30%)

09 Ingest and transform data

transform data by using Apache Spark

transform data by using Transact-SQL

transform data by using Data Factory

transform data by using Azure Synapse Pipelines

transform data by using Stream Analytics

cleanse data

split data

shred JSON

encode and decode data

configure error handling for the transformation

normalize and denormalize values

transform data by using Scala

perform data exploratory analysis

10 Design and develop a batch processing solution

develop batch processing solutions by using Data Factory, Data Lake, Spark, Azure Synapse Pipelines, PolyBase, and Azure Databricks

create data pipelines

design and implement incremental data loads

design and develop slowly changing dimensions

handle security and compliance requirements

scale resources

configure the batch size

design and create tests for data pipelines

integrate Jupyter/IPython notebooks into a data pipeline

handle duplicate data

handle missing data

handle late-arriving data

upsert data

regress to a previous state

design and configure exception handling

configure batch retention

design a batch processing solution

debug Spark jobs by using the Spark UI

11 Design and develop a stream processing solution

develop a stream processing solution by using Stream Analytics, Azure Databricks, and Azure Event Hubs

process data by using Spark structured streaming

monitor for performance and functional regressions

design and create windowed aggregates

handle schema drift

process time series data

process across partitions

process within one partition

configure checkpoints/watermarking during processing

scale resources

design and create tests for data pipelines

optimize pipelines for analytical or transactional purposes

handle interruptions

design and configure exception handling

upsert data

replay archived stream data

design a stream processing solution

12 Manage batches and pipelines

trigger batches

handle failed batch loads

validate batch loads

manage data pipelines in Data Factory/Synapse Pipelines

schedule data pipelines in Data Factory/Synapse Pipelines

implement version control for pipeline artifacts

manage Spark jobs in a pipeline

13 3. Design and Implement Data Security (10-15%)

Design and Implement Data Security (10-15%)

14 Design security for data policies and standards

design data encryption for data at rest and in transit

design a data auditing strategy

design a data masking strategy

design for data privacy

design a data retention policy

design to purge data based on business requirements

design Azure role-based access control (Azure RBAC) and POSIX-like Access Control List(ACL) for Data Lake Storage Gen2

design row-level and column-level security

15 Implement data security

implement data masking

encrypt data at rest and in motion

implement row-level and column-level security

implement Azure RBAC

implement POSIX-like ACLs for Data Lake Storage Gen2

implement a data retention policy

implement a data auditing strategy

manage identities, keys, and secrets across different data platform technologies

implement secure endpoints (private and public)

implement resource tokens in Azure Databricks

load a DataFrame with sensitive information

write encrypted data to tables or Parquet files

manage sensitive information

16 4. Monitor and Optimize Data Storage and Data Processing (10-15%)

Monitor and Optimize Data Storage and Data Processing (10-15%)

17 Monitor data storage and data processing

implement logging used by Azure Monitor

configure monitoring services

measure performance of data movement

monitor and update statistics about data across a system

monitor data pipeline performance

measure query performance

monitor cluster performance

understand custom logging options

schedule and monitor pipeline tests

interpret Azure Monitor metrics and logs

interpret a Spark directed acyclic graph (DAG)

18 Optimize and troubleshoot data storage and data processing

compact small files

rewrite user-defined functions (UDFs)

handle skew in data

handle data spill

tune shuffle partitions

find shuffling in a pipeline

optimize resource management

tune queries by using indexers

tune queries by using cache

optimize pipelines for analytical or transactional purposes

optimize pipeline for descriptive versus analytical workloads

troubleshoot a failed spark job

troubleshoot a failed pipeline run

Tools & Technologies

Every tool listed here is installed, configured and used in a hands-on lab session.

Core Tools

Hands-On Labs

Practical Environment

Industry-Standard Tools

Real-World Setup

Guided Exercises

Skill Building

Sample Datasets

Practice Material

Practice & Projects

Mini Projects

Applied Practice

Assignments

Mentor Reviewed

Doubt Sessions

Live Support

Career Readiness

Resume Building

Career Support

Mock Interviews

Interview Prep

Certification Prep

Global Recognition

Deployment & Delivery

Production Practices

Real-World Ready

Best Practices

Industry Standards

136+

Hands-On Lessons

Core Modules

40 hours

Training Duration

100%

Practical Training

You don't just learn Data Engineering on Microsoft Azure - DP 203. You ship it.

Three major projects, each mirroring how production teams actually work — from guided foundations to a portfolio-ready capstone.

PROJECT // 01

Guided Foundation Project

→Requirement Analysis

→Guided Implementation

→Mentor Review

→Iteration

Foundation Beginner

Apply the fundamentals in a structured, mentor-reviewed project

Take the core concepts from the first half of the curriculum and apply them to a realistic scenario, with guidance and feedback from your mentor at every step.

Structured project brief

Step-by-step implementation

Mentor feedback and review

Documented outcome

Stack Core Concepts Best Practices

PROJECT // 02

Applied Practice Project

→Scenario Design

→Independent Build

→Testing & Validation

→Peer Review

Applied Intermediate

Build a more independent project mirroring real production scenarios

Work through a project that combines multiple concepts from the curriculum, closer to how work is actually structured on the job — less hand-holding, more ownership.

End-to-end implementation

Testing and validation

Documentation

Peer/mentor review

Stack Applied Skills Testing

PROJECT // 03

Capstone Project

→Planning

→End-to-End Build

→Review & Refinement

→Presentation

Capstone Advanced

Take a project from requirements to a polished, portfolio-ready deliverable

Your final project — plan, build, test and present a complete solution using everything covered in the curriculum, reviewed by mentors before you graduate.

Complete working solution

Presentation-ready documentation

Mentor sign-off

Portfolio-ready deliverable

Stack Full Curriculum Portfolio

All 3 projects go directly into your portfolio & resume — reviewed by mentors before you graduate.

See Sample Project Reports

Upcoming Batches

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Why Radical Technologies

Live Online Training

Highly practical oriented training
Installation support on your system
24/7 Email and Phone support
100% Placement Assistance
Global Certification Preparation
Trainer-Student Interactive Portal
Assignments and Projects by Mentors

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Live Classroom Training

Weekend / Weekdays / Morning / Evening batches
80:20 Practical and Theory ratio
Real-life Case Studies
Easy make-up for missed sessions
PSI | Kryterion | Redhat Test Centers
Lifetime Video Classroom Access (coming soon)
Resume Prep and Mock Interviews

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Self-Paced Training

Learn 300+ courses at your own time
50,000+ Satisfied Learners
Course Completion Certificate
Practical Labs available
Mentor Support available
Doubt Clearing Session available
10% Discounted Global Certification

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Global Certification

Radical Technologies is the leading IT certification institute in Pune, offering globally recognized certifications across various domains. With expert trainers and comprehensive materials, we ensure students gain in-depth knowledge and hands-on experience to excel in their careers. Our certification programs are tailored to meet industry standards — from cloud technologies to data science — empowering individuals to stay ahead in the ever-evolving tech landscape.

Career Services

At Radical Technologies, we are committed to your success beyond the classroom. Our 100% Job Assistance program ensures that you are not only equipped with industry-relevant skills but also guided through the job placement process. With personalised resume building, interview preparation, and access to our extensive network of hiring partners, we help you take the next step confidently into your IT career.