AWS Data Engineer Course in Bangalore

Course Overview

This AWS Data Engineer Associate course follows the official DEA-C01 exam blueprint and industry job requirements. The course covers end-to-end data engineering on AWS from ingesting batch and streaming data to transforming, storing, cataloging, and analyzing large datasets. You’ll work on real-world labs including ETL pipeline creation, Glue crawlers, Redshift queries, data quality validation, automation, monitoring, and security. The curriculum is designed to make you certification-ready and job-ready for AWS data engineering roles.

End-to-end AWS data pipeline implementation

Real-world ETL and streaming use cases

Hands-on labs with AWS managed services

Focus on performance, security, and data governance

Ideal for enterprise and big-data projects

What Will You Learn

Design and implement data ingestion pipelines using AWS services

Consume data from streaming and batch sources like Kinesis, MSK, APIs, and databases.

Transform and process data using AWS Glue, EMR, Lambda, and Redshift.

Convert and optimize data formats such as CSV, Parquet, and columnar storage.

Choose the right data stores for analytics using S3, Redshift, DynamoDB, and Lake Formation.

Build and manage data catalogs using AWS Glue Data Catalog and crawlers.

Design scalable data models and handle schema evolution.

Automate data workflows using Step Functions, MWAA, and EventBridge

Query and analyze data using Amazon Athena and QuickSight

Monitor, log, and troubleshoot data pipelines using CloudWatch and CloudTrail.

Implement data quality checks and validation rules.

Secure data using IAM, KMS, Secrets Manager, and Lake Formation permissions

Apply encryption, masking, and privacy controls for sensitive data.

Implement governance strategies for compliance, auditing, and data sharing.

Prepare confidently for the AWS Certified Data Engineer – Associate exam.

Course Structure

Intended audience

This AWS Data Engineering Course in Bangalore is ideal for data engineers, ETL developers, analysts, and backend developers working with data pipelines. It is well suited for AWS professionals preparing for DEA-C01, big-data practitioners (Spark/Hadoop), and analysts transitioning into data engineering roles.

Prerequisites

Basic knowledge of AWS services such as S3 and EC2, programming skills in Python or SQL, and familiarity with relational or NoSQL databases are recommended. Prior data engineering experience is not mandatory; the course starts from ingestion fundamentals and builds up step by step.

Course Syllabus