Aws Data Engineer Bootcamp: The Complete Guide
Published 3/2026
Created by manish tiwari
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All Levels | Genre: eLearning | Language: English | Duration: 221 Lectures ( 28h 38m ) | Size: 17.2 GB
What you'll learn
✓ Master the core concepts of AWS Data Engineering and understand how modern data platforms are built on AWS
✓ Design and build end-to-end data pipelines on AWS from data ingestion to analytics
✓ Create scalable Data Lakes using Amazon S3 for storing structured and semi-structured data
✓ Perform ETL (Extract, Transform, Load) using AWS Glue with real-world practical examples
✓ Build serverless data pipelines using AWS Lambda
✓ Query datasets using Amazon Athena without managing servers
✓ Build event-driven architectures using Amazon SNS
✓ Monitor and troubleshoot pipelines using AWS CloudWatch
✓ Gain hands-on experience with AWS services used by professional Data Engineers
Requirements
● Basic understanding of computers and the internet
● No prior AWS experience is required - everything will be explained from scratch
● A computer with internet connection to access AWS services and practice the labs
Description
Master AWS Data Engineering - Build Real World Data Pipelines on AWS
Become a professional AWS Data Engineer by mastering the most important AWS data engineering services used by companies worldwide. This course is designed to help you build real-world data pipelines, data lakes, ETL workflows, streaming pipelines, and analytics solutions using AWS.
If you want to become an AWS Data Engineer, Cloud Data Engineer, Big Data Engineer, or prepare for AWS Data Analytics and AWS Data Engineer roles, this course will give you practical hands-on experience with the most important AWS services.
You will learn how to design and build end-to-end data engineering pipelines using AWS services like S3, Glue, Lambda, Kinesis, Redshift, Athena, EMR, SNS, CloudWatch and more.
This course focuses heavily on real-world projects and hands-on labs, so you will gain the practical skills needed to work as an AWS Data Engineer in production environments.
What You Will Learn
Build end-to-end AWS Data Engineering pipelines
Create Data Lakes using Amazon S3
Perform ETL using AWS Glue
Process big data using Amazon EMR
Build real-time streaming pipelines using Amazon Kinesis
Run serverless data pipelines using AWS Lambda
Query data using Amazon Athena
Build Data Warehouses using Amazon Redshift
Implement event-driven architectures using SNS and SQS
Monitor pipelines using AWS CloudWatch
Design production-grade AWS data architecture
Understand best practices for AWS Data Engineering
Work with structured and semi-structured data
Build batch and streaming data pipelines
Learn data lake architecture on AWS
Implement data ingestion, transformation, and analytics
AWS Services Covered in this Course
This course covers the most important AWS services used in Data Engineering and Big Data pipelines.
Data Storage
• Amazon S3
• Data Lake Architecture
ETL & Data Processing
• AWS Glue
• AWS Lambda
Streaming Data
• Amazon Kinesis
Big Data Processing
• Amazon EMR
• Spark on AWS
Data Analytics
• Amazon Athena
Monitoring & Automation
• AWS CloudWatch
• Event Driven Pipelines
Messaging & Notifications
• Amazon SNS
Real-World AWS Data Engineering
In this course you will build multiple real-world AWS data engineering projects such as
• Build a Data Lake on AWS S3
• Create ETL pipelines using AWS Glue
• Query data using Amazon Athena
• Build serverless pipelines using AWS Lambda
• Create event-driven architectures using SNS
• Monitor pipelines using CloudWatch
These projects simulate real production scenarios used by modern data engineering teams.
Why Learn AWS Data Engineering?
Data Engineering is one of the highest paying roles in cloud and big data.
Companies are rapidly moving their data platforms to AWS, and they need skilled AWS Data Engineers who can design scalable data lakes, ETL pipelines, and analytics systems.
By learning AWS Data Engineering, you can open career opportunities like
• AWS Data Engineer
• Cloud Data Engineer
• Big Data Engineer
• Data Platform Engineer
• Analytics Engineer
Who this course is for
■ Aspiring AWS Data Engineers who want to build real-world data pipelines on AWS
■ Data Engineers who want to learn or upgrade their skills in AWS Data Engineering services
■ Cloud Engineers who want to specialize in Data Engineering on AWS
■ ETL Developers who want to transition into modern cloud data engineering
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