Data Engineering

★★★★★

(2,095 ratings) 50,000+ Student

CLOUDERA DATA ENGINEERING WITH APACHE ICEBERG

The Cloudera Data Engineering with Apache Iceberg course is designed for professionals who want to build modern data engineering skills using Cloudera CDP, Apache Iceberg, Spark, Hive, Kafka, and Airflow. The training focuses on creating scalable data pipelines, managing large data lakes, designing lakehouse architectures, and processing both batch and streaming data. Through hands-on projects and real-world scenarios, learners gain practical experience in ETL/ELT development, data governance, performance optimization, and cloud data engineering. This course is ideal for data engineers, Spark developers, ETL professionals, cloud data engineers, data architects, and anyone looking to build expertise in modern enterprise data platforms.

Radical Technologies

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

Online / Classroom

IT Training Programme

Duration 50 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

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

50 hours

Training Duration

Core Modules

273

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

25 sections • 273 lessons • 50 hours

Jump to Section

Total Duration

50 hours

100% Practical · Unlimited Doubt Sessions

01 Cloudera Data Engineering with Apache Iceberg Training Program

(CDP + Spark + Hive + Apache Iceberg + Kafka + Airflow + Data Governance +

Cloud Data Engineering)

Duration: 40–50 Hours

Projects: 5 Enterprise Projects

Assignments: 12 Hands-On Assignments

Job-Oriented Scenarios: 15 Real-World Industry Scenarios

Outcome: Become a modern Data Engineer capable of building enterprise-scale Lakehouse

platforms using Cloudera CDP and Apache Iceberg.

02 Target Audience

• Data Engineers

• Big Data Developers

• Hadoop Administrators

• Spark Developers

• ETL Developers

• Cloud Data Engineers

• Database Professionals

• Data Architects

03 🎯 Program Objectives

By the end of this training, participants will be able to:

✅ Build Enterprise Data Pipelines using Cloudera CDP

✅ Work with Apache Iceberg Tables

✅ Design Lakehouse Architectures

✅ Implement Data Ingestion Frameworks

✅ Manage Large-Scale Data Lakes

✅ Build ETL/ELT Pipelines using Spark

✅ Perform Data Governance & Metadata Management

✅ Optimize Query Performance

✅ Handle Streaming and Batch Data Processing

04 Module 1: Data Engineering Fundamentals

Topics

Introduction to Data Engineering

• Data Warehouse Concepts

• Data Lake Concepts

• Lakehouse Architecture

• ETL vs ELT

• Data Engineering Lifecycle

Big Data Fundamentals

• Structured Data

• Semi-Structured Data

• Unstructured Data

Assignment

›Design Enterprise Data Architecture.

Job Scenario

›Create a modern data platform for a retail company.

05 Module 2: Cloudera Data Platform (CDP) Architecture

Topics

Introduction to CDP

CDP Components

• Data Hub

• Data Warehouse

• Data Engineering

• Data Flow

• Data Catalog

CDP Deployment Models

• Public Cloud

• Private Cloud

• Hybrid Cloud

Security Architecture

Practical Lab

Explore CDP Environment.

Assignment

›Build CDP Reference Architecture.

06 Module 3: Hadoop Ecosystem Fundamentals

Topics

HDFS Architecture

YARN

Hive

HBase

Sqoop

ZooKeeper

Spark Overview

Lab

Manage Hadoop Environment.

Assignment

›Deploy Sample Hadoop Workflow.

07 Module 4: Apache Spark for Data Engineering

Topics

Spark Architecture

RDD

DataFrames

Spark SQL

Transformations

Actions

Spark Optimization

Partitioning

Practical Lab

Develop Spark Applications.

Assignment

›Process Large Datasets using Spark.

Job Scenario

›Build scalable ETL pipeline.

08 Module 5: Software Channel Management

Topics

Hive Architecture

Hive Metastore

Partitioning

Bucketing

Query Optimization

ACID Tables

Practical Lab

Create Enterprise Data

Warehouse.

Assignment

›Design Sales Data
›Warehouse.

09 Module 6: Apache Iceberg Fundamentals

Topics

Introduction to Iceberg

Why Iceberg?

Iceberg vs Hive Tables

Iceberg vs Delta Lake

Iceberg vs Hudi

Table Formats

Hidden Partitioning

Snapshot Architecture

Time Travel

Schema Evolution

Practical Lab

Create Iceberg Tables.

Assignment

›Build Lakehouse Table Structure.

Job Scenario

›Migrate Legacy Hive Tables to Iceberg
›

10 Module 7: Apache Iceberg Advanced Features

Topics

Snapshots

Branching

Tagging

Rollbacks

Incremental Reads

Metadata Management

Partition Evolution

Data File Management

Practical Lab

Implement Time Travel Queries.

Assignment

›Create Version-Controlled Data Lake.

11 Module 8: Data Ingestion Frameworks

Topics

Batch Ingestion

Real-Time Ingestion

CDC (Change Data Capture)

Kafka Integration

Database Connectors

API-Based Ingestion

Practical Lab

Ingest Data into Iceberg Tables.

Assignment

›Build Data Ingestion Pipeline.

Job Scenario

›Load ERP data into Data Lakehouse.

12 Module 9: Data Transformation & ETL Development

Topics

Data Cleansing

Data Enrichment

Data Validation

Data Standardization

Data Quality Checks

Spark ETL Framework

Practical Lab

Develop ETL Jobs.

Assignment

›Build Customer Data Pipeline.

13 Module 10: Data Governance & Metadata Management

Topics

Data Governance Fundamentals

Metadata Management

Data Catalog

Lineage Tracking

Data Classification

Compliance Management

Cloudera Data Catalog

Apache Atlas

Practical Lab

Implement Data Governance.

Assignment

›Create Enterprise Data Catalog.

Job Scenario

Ensure regulatory compliance.

14 Module 11: Security & Access Management

Topics

Authentication

Authorization

Ranger Overview

Role-Based Access Control

Encryption

Auditing

Practical Lab

Configure Data Security Policies.

Assignment

›Implement Data Access Controls.

15 Module 12: Workflow Orchestration

Topics

Apache Airflow

Cloudera Workflows

Scheduling

Dependency Management

Monitoring

Error Handling

Practical Lab

Automate ETL Pipelines.

Assignment

›Build Workflow Automation.
›

16 Module 13: Performance Optimization

Topics

Query Optimization

Spark Optimization

Iceberg Performance Tuning

Partition Strategy

Compaction

Resource Optimization

Practical Lab

Optimize Data Processing Workloads.

Assignment

›Improve ETL Performance.

Job Scenario

›Reduce ETL processing time by 50%.

17 Module 14: Streaming Data Engineering

Topics

Kafka Fundamentals

Spark Structured Streaming

Real-Time Processing

Event-Driven Architecture

Iceberg Streaming Integration

Practical Lab

Real-Time Data Pipeline.

Assignment

›Build Streaming ETL System.

18 Module 15: Cloud Data Engineering with Cloudera

Topics

AWS Integration

Azure Integration

GCP Integration

Object Storage

• Amazon S3

• Azure ADLS

• Google Cloud Storage

Hybrid Data Platforms

Practical Lab

Deploy Lakehouse in Cloud.

Assignment

›Design Multi-Cloud Data Architecture.

19 Module 16: Data Observability & Monitoring

Topics

Pipeline Monitoring

Data Quality Monitoring

Alerting

Logging

SLA Monitoring

Operational Dashboards

Practical Lab

Build Monitoring Dashboard.

20 🚀 Industry Projects

Project 1: Retail Data Lakehouse using Iceberg

Deliverables

• Customer Data Lake

• Sales Data Lakehouse

• Time Travel Reporting

• Governance Framework

Project 2: Banking Data Platform

Deliverables

• Transaction Processing

• CDC Pipelines

• Compliance Reporting

• Metadata Catalog

Project 3: Healthcare Data Lakehouse

Deliverables

• Patient Data Integration

• Data Quality Framework

• Secure Access Controls

Project 4: Real-Time Streaming Analytics Platform

Deliverables

• Kafka Integration

• Spark Streaming

• Iceberg Storage

• Dashboard Reporting

Project 5: Enterprise Data Modernization

Deliverables

• Hive-to-Iceberg Migration

• Performance Optimization

• Governance Implementation

21 📝 Practical Assignments

Assignment 1

›Design Data Lake Architecture

Assignment 2

›Create Spark ETL Pipeline

Assignment 3

›Build Hive Data Warehouse

Assignment 4

›Implement Iceberg Tables

Assignment 5

›Perform Time Travel Queries

Assignment 6

›Create CDC Pipeline

Assignment 7

›Configure Ranger Security

Assignment 8

›Build Metadata Catalog

Assignment 9

›Develop Airflow Workflows

Assignment 10

›Optimize Iceberg Performance

Assignment 11

›Implement Streaming Pipeline

Assignment 12

›Deploy Cloud Data Platform

22 💼 Real-Time Job-Oriented Scenarios

Scenario 1

›Migrate Hive Data Warehouse to Apache Iceberg.

Scenario 2

›Build Lakehouse architecture for banking data.

Scenario 3

›Implement CDC from Oracle to Iceberg.

Scenario 4

›Create time-travel reporting solution.

Scenario 5

›Design secure healthcare data platform.

Scenario 6

›Implement enterprise data governance.

Scenario 7

›Optimize Spark jobs processing 10TB+ data.

Scenario 8

›Build Kafka real-time analytics platform.

Scenario 9

›Manage schema evolution without downtime.

Scenario 10

›Reduce cloud storage costs through Iceberg optimization.

Scenario 11

›Build enterprise metadata management solution.

Scenario 12

›Implement regulatory compliance controls.

Scenario 13

›Handle large-scale partition evolution.

Scenario 14

›Perform disaster recovery for data platform.

Scenario 15

›Deploy hybrid cloud data lakehouse.

23 🛠 Technologies Covered

Cloudera Platform

• Cloudera CDP

• Cloudera Data Engineering

• Cloudera Data Warehouse

• Cloudera Data Catalog

Big Data

• Hadoop

• HDFS

• Hive

• Spark

Lakehouse

• Apache Iceberg

• Hive Tables

• Parquet

• ORC

Streaming

• Apache Kafka

• Spark Structured Streaming

Governance

• Apache Atlas

• Ranger

Workflow

• Apache Airflow

Cloud

• AWS S3

• Azure Data Lake Storage

• Google Cloud Storage

24 🎯 Career Opportunities

• Cloudera Data Engineer

• Big Data Engineer

• Apache Spark Developer

• Lakehouse Engineer

• Data Platform Engineer

• Hadoop Developer

• Cloud Data Engineer

• ETL Developer

• Data Architect

• Analytics Engineer

25 🎓 Recommended Certification Path

Cloudera Certifications

• Cloudera Data Platform (CDP)

• Cloudera Data Engineer Certification

• Cloudera Administrator Certification

Complementary Certifications

• Apache Spark Certification

• AWS Data Engineer Associate

• Microsoft Azure Data Engineer (DP-203)

• Databricks Data Engineer Associate

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

273+

Hands-On Lessons

Core Modules

50 hours

Training Duration

100%

Practical Training

You don't just learn CLOUDERA DATA ENGINEERING WITH APACHE ICEBERG. 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

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Weekend / Weekdays / Morning / Evening batches
80:20 Practical and Theory ratio
Real-life Case Studies
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Learn 300+ courses at your own time
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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.