AWS Data Engineering Training
1K+ ReviewsInstructor-Led Training Parameters
Course Highlights
- Instructor-led Online Training
- Project Based Learning
- Certified & Experienced Trainers
- Course Completion Certificate
- Lifetime e-Learning Access
- 24x7 After Training Support
AWS Data Engineering Training Course Overview
AWS Data Engineering is the study of Data Pipelines, Data Storage, and Data Transfer. Multisoft Systems has come up with AWS Data Engineering Training to promote the careers of Data Engineers, Data Scientists, Solutions Architects, and Data Analysts. This course will help you in learning the techniques of hosting big data and performing distributed processing on the AWS platform. To pursue this AWS Data Engineering Training, an aspirant needs to carry a fundamental level understanding of big data and Hadoop concepts and basic knowledge of AWS technical essentials.
Our offered course is developed by industry expert trainers to give in-depth knowledge of AWS Cloud Economics, Amazon DynamoDB, AWS Virtuous Cycle, Amazon DynamoDB, Kinesis Firehose, Knowledge Checks, DynamoDB Stream, EMR Operations, Spark Components, AWS Data Pipeline, RedShift Architecture. It is aligned with the AW Certified Data Analytics exam.
AWS Data Engineering Course Objectives:
- How to work with AWS Cloud Architecture Design Principles?
- How do I use Amazon EMR to process data with the use of Hadoop ecosystem tools
- How do I use Amazon Kinesis for big data processing in real-time?
- How to use Kinesis Streams to analyze and transform big data?
- How to use Amazon QuickSight to visualize data and perform queries?
- How to load Data into Kinesis Stream?
AWS Data Engineering Online Training
- 32 Hrs. Instructor-led Online Training
- Recorded Videos After Training
- Digital Learning Material
- Course Completion Certificate
- Lifetime e-Learning Access
- 24x7 After Training Support
Target Audience
- Data Engineers
- Data Scientists
- Solutions Architects
- Data Analysts
AWS Data Engineering Course Prerequisites
- Basic knowledge of AWS technical essentials
- A fundamental level understanding of big data and Hadoop concepts
AWS Data Engineering Course Certification
- Multisoft Systems will provide you with a training completion certificate after completing this AWS Data Engineering Training.
Instructor-led Training Live Online Classes
Suitable batches for you
| Apr, 2026 | Weekdays | Mon-Fri | Enquire Now |
| Weekend | Sat-Sun | Enquire Now | |
| May, 2026 | Weekdays | Mon-Fri | Enquire Now |
| Weekend | Sat-Sun | Enquire Now |
AWS Data Engineering Training Course Content
Module 1: AWS in Big Data introduction
- Introduction to Cloud Computing
- Cloud Computing Deployments Models
- Amazon Web Services Cloud Platform
- The Cloud Computing Difference
- AWS Cloud Economics
- AWS Virtuous Cycle
- AWS Cloud Architecture Design Principles
- Why AWS for Big Data - Reasons
- Why AWS for Big Data - Challenges
- Databases in AWS
- Relational vs Non-Relational Databases
- Data Warehousing in AWS
- Services for Collecting, Processing, Storing, and Analyzing Big Data
- Amazon Redshift
- Amazon Kinesis
- Amazon EMR
- Amazon DynamoDB
- Amazon Machine Learning
- AWS Lambda
- Amazon Elasticsearch Service
- Amazon EC2 (big data analytics software on EC2 instances)
- Amazon Redshift
- Amazon Kinesis
- Amazon EMR
- Amazon DynamoDB
- Amazon Machine Learning
- AWS Lambda
- Amazon Elasticsearch Service
- Amazon EC2 (big data analytics software on EC2 instances)
- Key Takeaway
- Knowledge Checks
- Lesson End Project
Module 2 - Collection
- Objectives
- Amazon Kinesis Fundamentals
- Loading Data into Kinesis Stream
- Kinesis Data Stream High-Level Architecture
- Kinesis Stream Core Concepts
- Kinesis Stream Emitting Data to AWS Services
- Kinesis Connector Library
- Kinesis Firehose
- Transferring Data Using Lambda
- Amazon SQS
- IoT and Big Data
- IoT Framework
- AWS Data Pipeline
- AWS Data Pipeline Components
- Key Takeaway
- Knowledge Checks
- Lesson End Project
Module 3 - Storage
- Objectives
- Introduction to AWS Big Data Storage Services
- Amazon Glacier
- Glacier and Big Data
- DynamoDB Introduction
- The Architecture of the DynamoDB Table
- DynamoDB in AWS Ecosystem
- DynamoDB Partitions
- Data Distribution
- Local Secondary Index (LSI) **
- Global Secondary Index (GSI) **
- DynamoDB GSI vs LSI
- DynamoDB Stream
- Cross-Region Replication in DynamoDB
- Partition Key Selection
- Snowball & AWS Big Data
- AWS DMS
- AWS Aurora in Big Data
- Key Takeaway
- Knowledge Checks
- Lesson End Project
Module 4 - Processing I
- Objectives
- Introduction to AWS Big Data Processing Services
- Amazon Elastic MapReduce (EMR)
- Apache Hadoop
- EMR Architecture
- Storage Options
- EMR File Storage and Compression
- Supported File Format and File Size
- Single-AZ Concept
- EMR Operations
- EMR Releases
- AWS Cluster
- Launching a Cluster
- Advanced EMR Setting Option
- Choosing Instance Type
- Number of Instances
- Monitoring EMR
- Resizing of Cluster
- Using Hue with EMR
- Setup Hue for LDAP
- Hive on EMR
- Hive Use Cases
- Key Takeaway
- Knowledge Checks
- Lesson End Project
Module 5: Processing II
- HBase with EMR
- HBase Use Cases
- Comparison of HBase with Redshift and DynamoDB
- HBase Architecture HBase on S3
- HBase and EMRFS
- HBase Integration
- HCatalog
- Presto with EMR
- Advantages of Presto
- Presto Architecture
- Spark with EMR
- Spark Use Cases
- Spark Components
- Spark Integration With EMR
- AWS Lambda in AWS Big Data Ecosystem
- Limitations of Lambda
- Lambda and Kinesis Stream
- Lambda and Redshift
- Key Takeaway
- Knowledge Checks
- Lesson End Project
Module 6: Analysis I
- Objectives
- Introduction to AWS Big Data Analysis Services
- RedShift
- RedShift Architecture
- RedShift in the AWS Ecosystem
- Columnar Databases
- RedShift Table Design
- RedShift Workload Management
- RedShift Loading Data
- RedShift Maintenance and Operations
- Key Takeaway
- Knowledge Checks
- Lesson End Project
Module 7: Analysis II
- Machine Learning
- Machine Learning - Use Cases
- Algorithms
- Amazon SageMaker
- Elasticsearch
- Amazon Elasticsearch Service
- Loading of Data into Elasticsearch
- Logstash
- Kibana
- RStudio
- Characteristics
- Athena
- Presto and Hive
- Integration with AWS Glue
- Comparison of Athena with Other AWS Services
- Lab Run Query on S3 Using Serverless Athena
- Key Takeaway
- Knowledge Checks
- Lesson End Project
Module 8: Visualisation
- Objectives
- Introduction to AWS Big Data Visualization Services
- Amazon QuickSight
- Amazon QuickSight - Use Cases
- LAB Create an Analysis with a Single Visual Using Sample Data
- Working with Data
- Assisted Practice: TBD
- QuickSight Visualization
- Big Data Visualization
- Apache Zeppelin
- Jupyter Notebook
- Comparison Between Notebooks
- D3.js (Data-Driven Documents)
- MicroStrategy
- Key Takeaway
- Knowledge Checks
- Lesson End Project
Module 9: Security
- Objectives
- Introduction to AWS Big Data Security Services
- EMR Security
- Roles
- Private Subnet
- Encryption At Rest and In Transit
- RedShift Security
- KMS Overview
- SloudHSM
- Limit Data Access
- STS and Cross Account Access
- Cloud Trail
- Key Takeaway
- Knowledge Checks
- Lesson End Project
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AWS Data Engineering Training (MCQ) Assessment
This assessment tests understanding of course content through MCQ and short answers, analytical thinking, problem-solving abilities, and effective communication of ideas. Some Multisoft Assessment Features :
- User-friendly interface for easy navigation
- Secure login and authentication measures to protect data
- Automated scoring and grading to save time
- Time limits and countdown timers to manage duration.
AWS Data Engineering Corporate Training
Employee training and development programs are essential to the success of businesses worldwide. With our best-in-class corporate trainings you can enhance employee productivity and increase efficiency of your organization. Created by global subject matter experts, we offer highest quality content that are tailored to match your company’s learning goals and budget.
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Certification Training Achievements: Recognizing Professional Expertise
Multisoft Systems is the “one-top learning platform” for everyone. Get trained with certified industry experts and receive a globally-recognized training certificate. Some Multisoft Training Certificate Features :
- Globally recognized certificate
- Course ID & Course Name
- Certificate with Date of Issuance
- Name and Digital Signature of the Awardee
AWS Data Engineering Training Trainer Profile
19+ Years Experienced
Our AWS Data Engineering Corporate & Certification Program trainers bring 13+ years of proven industry expertise, delivering practical insights aligned with real project environments.
Trained 3950+ Professionals
Our expert trainers have successfully trained 3350+ professionals through structured, real-time training programs designed for industry readiness and career growth.
Certified Experts & Real-Time Project Learning
Build strong practical skills through live project-based training sessions led by certified industry experts with real-world experience.
Hands-on Learning Approach
Gain practical exposure through real-time scenarios, industry case studies, and hands-on assignments that simulate actual project challenges.
Certification Training Guidance
Receive expert support to prepare effectively, practice strategically, and confidently achieve globally recognized certification success.
Customized Training Delivery
Flexible training approach tailored to individual learning goals, skill levels, and evolving industry requirements for maximum effectiveness.
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