Data Engineering & Big Data with AWS Training

Course Overview

This course is designed for professionals and aspiring data engineers who want to build, manage, and optimize data pipelines using big data tools and AWS cloud services. You’ll learn to design scalable data architecture and handle batch and real-time data processing using tools like Apache Spark, AWS Glue, S3, Redshift, Kinesis, and more.

What You Will Learn

• Introduction to Data Engineering and Data Lakes
• Big Data Ecosystem: Hadoop, Hive, HDFS basics
• Apache Spark for distributed computing
• AWS S3: Data storage & security
• AWS Glue: ETL pipelines and data catalog
• AWS Redshift: Data warehousing and analytics
• Amazon EMR for large-scale processing
• AWS Lambda & Kinesis for real-time data streaming
• Building end-to-end pipelines (batch + real-time)
• Data modeling, partitioning, and performance tuning

Hands-On Projects

• ETL Pipeline from S3 to Redshift using AWS Glue
• Real-Time Log Processing using Kinesis + Lambda
• Customer Segmentation Dashboard on Redshift + QuickSight
• Big Data Analysis using Apache Spark on EMR

Eligibility Criteria

• Graduates from Computer Science, IT, or Data Science background
• Working professionals in analytics, data warehousing, or IT
• Developers looking to move into data engineering
• Basic Python/SQL knowledge is recommended

Job Roles After This Course

• Data Engineer
• Big Data Developer
• Cloud Data Engineer – AWS
• ETL Developer / Data Pipeline Engineer
• DevOps Engineer (Data Pipelines)

Top recruiters: Amazon, Deloitte, Infosys, Wipro, TCS, Capgemini, Cognizant, and many product-based startups using AWS.