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AWS Data Engineer-Associate (DEA-C01) Course

Professional working on a laptop with cloud computing technology
Edoxi's AWS Data Engineer-Associate (DEA-C01) Course provides hands-on training to help you build, manage, and secure scalable data pipelines on AWS. Learn to work with Amazon S3, AWS Glue, Redshift, Kinesis, EMR, Lambda, Athena, and QuickSight through practical labs and real-world projects. Prepare for the DEA-C01 certification exam, earn our course completion certificate, and advance your cloud data engineering career. Enrol now!
Course Duration
40 Hours
Corporate Days
5 Days
Learners Enrolled
50+
Modules
13
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Course Rating
5
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Mode of Delivery
Online
Certification by
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What Do You Learn from Edoxi's AWS Data Engineer-Associate Training

Design Scalable Data Pipelines
Illustrate comprehensive data pipelines using AWS services like Kinesis, Lambda and Glue to meet diverse use cases. Implement architecture patterns that optimise for throughput and reliability.
Implement Security and Governance
Identify risks and implement approaches to secure data across pipeline stages using AWS security services. Establish governance frameworks that maintain compliance throughout data transformations.
Master Data Storage Solutions
Select optimal storage options from S3-based Data Lakes to Redshift Data Warehouses based on analytics requirements. Apply partitioning strategies that enhance query performance and reduce costs.
Process Multi-Format Data
Implement pipelines that process structured, semi-structured and unstructured data using AWS Glue ETL jobs.
Maintain Data Integrity
Create workflows that preserve data integrity across format transformations.
Leverage Big Data Technologies
Explain MapReduce concepts and implement EMR clusters running Apache Hadoop and Apache Spark. Configure distributed processing environments that scale to handle petabyte-scale datasets.

About Our AWS Data Engineer-Associate (DEA-C01) Certification Course

Edoxi provides a specialised 40-hour AWS Data Engineering-Associate certification course. This intermediate-level training focuses on building scalable data pipelines in the AWS cloud. It teaches essential skills needed to implement modern data architectures. 

Our training features hands-on AWS labs where participants work with services like Amazon Kinesis, AWS Glue, Amazon Redshift, S3, and EMR. Participants also work with AWS Lambda and Step Functions to automate workflows, and use tools like Athena and QuickSight to analyse and visualise data. 

Through practical exercises, students learn to ingest, store, process, and analyse data at scale while implementing security best practices and governance frameworks. The AWS Data Engineer-Associate(DEA-C01) corporate training is ideal for IT professionals with experience in SQL and databases. It is also suitable for corporate teams looking to upskill their staff in cloud-based data engineering.

This training prepares participants for the AWS Certified Data Engineer-Associate exam, DEA-C01, while developing practical skills applicable across industries. 

Details of the AWS Data Engineer-Associate Certification Exam:

Exam Criteria Details
Exam Code DEA-C01
Exam Name AWS Certified Data Engineer Associate
Duration 130 minutes
Number of Questions 65, Multiple Choice
Passing Score 720/1000
Fees $150
Certification Validity 3 Years
Recertification Required 3 Years
Exam Administration Authority Pearson VUE

By completing the AWS Data Engineer-Associate(DEA-C01) course, you gain practical knowledge in ETL/ELT processes and integration with machine learning workflows through the comprehensive curriculum, which covers both batch and streaming approaches,

To learn more about AWS Data Engineer-Associate(DEA-C01) course fees, syllabus, or upcoming schedules, contact our team at Edoxi.

Features of Edoxi's AWS Data Engineer-Associate (DEA-C01) Training

AWS Lab Environment Access

Practice with authentic AWS services through dedicated lab subscriptions, providing hands-on experience with the complete AWS data ecosystem.

Comprehensive Study Materials

Get detailed student guides, courseware, and PDF resources covering Glue Crawlers, PySpark/Scala, Redshift Spectrum and other core data engineering tools.

Interactive Group Exercises

Participate in presentations and collaborative problem-solving sessions that simulate real-world data engineering scenarios.

Practical Hands-On Labs

Complete projects across the data pipeline spectrum with documented screenshots to build your portfolio of AWS implementations.

Industry-Standard Technologies

Work with core AWS services, including Kinesis, Glue, Redshift, EMR, and Lambda, that form the backbone of modern data architectures.

Certification Alignment

Course content directly maps to the AWS Certified Data Engineer-Associate exam(DEA-C01) objectives, preparing you for certification success.

Who Can Join Our AWS Data Engineer-Associate Training?

Data Analysts and Scientists

Professionals working with data who want to expand their skillset to include cloud-based data pipeline development and management on AWS.

ETL Developers

Developers with experience in data transformation processes who are looking to transition their skills to AWS cloud-native solutions.

IT Professionals with SQL Experience

Technology specialists with a strong foundation in database concepts and SQL who want to specialise in modern data architecture.

Machine Learning Practitioners

ML specialists seeking to understand the data engineering foundations that support effective machine learning pipelines.

Cloud Engineers

Technical professionals with cloud experience wanting to specialise in the high-demand field of data engineering.

Career Transitioners

Technology professionals looking to move into the rapidly growing field of cloud data engineering with AWS expertise.

AWS Data Engineer-Associate (DEA-C01) Course Modules

Module 1: Welcome to AWS Academy Data Engineering
  • Chapter 1: Course Introduction

    • Lesson 1.1: Course prerequisites and objectives
    • Lesson 1.2: Course overview
Module 2: Data-Driven Organisations
  • Chapter 1: Understanding Data-Driven Decisions

    • Lesson 2.1: Data-driven decisions
    • Lesson 2.2: The data pipeline – infrastructure for data-driven decisions
    • Lesson 2.3: The role of the data engineer in data-driven organisations
    • Lesson 2.4: Modern data strategies
Module 3: The Elements of Data
  • Chapter 1: The Five Vs of Data

    • Lesson 3.1: Volume and velocity
    • Lesson 3.2: Variety – data types
    • Lesson 3.3: Variety – data sources
    • Lesson 3.4: Veracity and value
    • Lesson 3.5: Activities to improve veracity and value
    • Lesson 3.6: Activity: Planning your pipeline
Module 4: Design Principles and Patterns for Data Pipelines
  • Chapter 1: Designing Modern Data Architectures

    • Lesson 4.1: AWS Well-Architected Framework and lenses
    • Lesson 4.2: Activity: Using the Well-Architected Framework
    • Lesson 4.3: The evolution of data architectures
    • Lesson 4.4: Modern data architecture on AWS
    • Lesson 4.5: Modern data architecture pipeline: Ingestion and storage
    • Lesson 4.6: Modern data architecture pipeline: Processing and consumption
    • Lesson 4.7: Streaming analytics pipeline
Module 5: Securing and Scaling the Data Pipeline
  • Chapter 1: Security and Scalability

    • Lesson 5.1: Cloud security review
    • Lesson 5.2: Security of analytics workloads
    • Lesson 5.3: ML security
    • Lesson 5.4: Scaling – an overview
    • Lesson 5.5: Creating a scalable infrastructure
    • Lesson 5.6: Creating scalable components
Module 6: Ingesting and Preparing Data
  • Chapter 1: ETL and Data Preparation

    • Lesson 6.1: ETL and ELT comparison
    • Lesson 6.2: Data wrangling introduction
    • Lesson 6.3: Data discovery
    • Lesson 6.4: Data structuring
    • Lesson 6.5: Data cleaning
    • Lesson 6.6: Data Enriching
    • Lesson 6.7: Data validating
    • Lesson 6.8: Data publishing
Module 7: Ingesting by Batch or by Stream
  • Chapter 1: Batch and Stream Ingestion Techniques

    • Lesson 7.1: Comparing batch and stream ingestion
    • Lesson 7.2: Batch ingestion processing
    • Lesson 7.3: Purpose-built ingestion tools
    • Lesson 7.4: AWS Glue for batch ingestion processing
    • Lesson 7.5: Scaling considerations for batch processing
    • Lesson 7.6: Lab: Performing ETL on a dataset using AWS Glue
    • Lesson 7.7: Kinesis for stream processing
    • Lesson 7.8: Scaling considerations for stream processing
    • Lesson 7.9: Ingesting IoT data by stream
Module 8: Storing and Organising Data
  • Chapter 1: Data Storage Solutions

    • Lesson 8.1: Storage in the modern data architecture
    • Lesson 8.2: Data lake storage
    • Lesson 8.3: Data warehouse storage
    • Lesson 8.4: Purpose-built databases
    • Lesson 8.5: Storage in support of the pipeline
    • Lesson 8.6: Securing storage
Module 9: Processing Big Data
  • Chapter 1: Big Data Processing Frameworks

    • Lesson 9.1: Big data processing concepts
    • Lesson 9.2: Apache Hadoop
    • Lesson 9.3: Apache Spark
    • Lesson 9.4: Amazon EMR
    • Lesson 9.5: Managing your Amazon EMR clusters
    • Lesson 9.6: Lab: Processing logs using Amazon EMR
    • Lesson 9.7: Apache Hudi
Module 10: Processing Data for ML
  • Chapter 1: Machine Learning Pipelines

    • Lesson 10.1: ML concepts
    • Lesson 10.2: The ML lifecycle
    • Lesson 10.3: Framing the ML problem to meet the business goal
    • Lesson 10.4: Collecting data
    • Lesson 10.5: Applying labels to training data with known targets
    • Lesson 10.6: Activity: Labelling with SageMaker Ground Truth
    • Lesson 10.7: Preprocessing data
    • Lesson 10.8: Feature engineering
    • Lesson 10.9: Developing a model
    • Lesson 10.10: Deploying a model
    • Lesson 10.11: ML infrastructure on AWS
    • Lesson 10.12: SageMaker
    • Lesson 10.13: Demo: Preparing data and training a model with SageMaker
    • Lesson 10.14: Demo: Preparing data and training a model with SageMaker Canvas
    • Lesson 10.15: AI/ML services on AWS
Module 11: Analysing and Visualising Data
  • Chapter 1: Data Analysis and Visualisation

    • Lesson 11.1: Considering factors that influence tool selection
    • Lesson 11.2: Comparing AWS tools and services
    • Lesson 11.3: Demo: Analysing and visualising data with AWS IoT Analytics and QuickSight
    • Lesson 11.4: Selecting tools for a gaming analytics use case
Module 12: Automating the Pipeline
  • Chapter 1: Automation in Data Engineering

    • Lesson 12.1: Automating infrastructure deployment
    • Lesson 12.2: CI/CD
    • Lesson 12.3: Automating with Step Functions
Module 13: Bridging to Certification
  • Chapter 1: AWS Certification Preparation

    • Lesson 13.1: AWS Certification overview

Download AWS Data Engineer-Associate (DEA-C01) Course Brochure

Lab Activities Involved in the AWS Data Engineer-Associate Training Course

Edoxi’s 40-hour Online AWS Data Engineering course delivers fully practical, subscription-based AWS Lab experiences. Here are the major hands-on labs in the AWS Data Engineer-Associate Training

Real-Time Data Streaming with Kinesis

Create an Amazon Kinesis Data Streams-based system that captures, processes, and analyses real-time data from multiple sources for immediate insights.

Serverless Event Processing

Schedule AWS Lambda functions using EventBridge to implement automated, serverless data processing workflows that operate on predefined schedules.

Data Security and Compliance

Discover sensitive information using Amazon Macie and implement data protection for S3 and EBS volumes using AWS KMS encryption services.

ETL Pipeline Development

Conduct data extraction, transformation, and loading tasks in AWS Glue, utilising Amazon S3 as source and destination for processed datasets.

Data Warehouse Implementation

Build an Amazon Redshift data warehouse with appropriate schema design, including security implementation for database credentials and monitoring.

Distributed Data Processing

Set up an Amazon EMR cluster and launch Spark jobs to process large-scale datasets using distributed computing frameworks for efficient analysis.

AWS Data Engineer-Associate Course Outcomes and Career Opportunities

Completing Edoxi’s 40-hour AWS Data Engineer–Associate certification course provides a structured pathway to high-growth roles in cloud and data engineering. Here are the major course outcomes 

Course Outcome Image
Gain globally relevant cloud data engineering skills by learning to build, secure, and scale data pipelines using core AWS services for international business environments.
Design and manage complete data workflows, from ingestion and storage to processing, analytics, and automation. Align your capabilities with global cloud architecture standards.
Develop proficiency in widely used AWS tools such as Kinesis, Glue, Redshift, EMR, and QuickSight, enabling you to work confidently within multinational organisations and global cloud ecosystems.
Strengthen your employability worldwide, becoming qualified for data engineering, cloud analytics, and big data roles across global enterprises, consulting firms, and technology companies.
Build strong readiness for the AWS Data Engineer–Associate certification, earning a credential that is recognised and valued in the global tech industry.
Apply practical problem-solving skills through hands-on labs and real datasets. Learn to handle complex data challenges in international supply chains, distributed systems, and cross-border digital operations.

Career Opportunities After Our AWS Data Engineer-Associate Certification

  • AWS Data Engineer
  • Cloud Data Engineer
  • Big Data Engineer
  • ETL Developer / ETL Engineer
  • Data Analytics Engineer
  • Machine Learning Data Engineer
  • Business Intelligence (BI) Engineer
  • Cloud Solutions Architect – Data Track
  • Data Warehouse Engineer
  • Data Platform Engineer

AWS Data Engineer-Associate (DEA-C01) Training Option

Live Online Training

  • 40 hours of Real-Time Instructor Interaction

  • Access AWS Cloud Lab Environment Remotely

  • Flexible Scheduling for Professionals

  • Virtual Classroom with Interactive Elements

Corporate Training

  • 5 days of Customised Training option for Team Requirements

  • Flexible Delivery Options (On-Site / Edoxi Office / Hotel)

  • Fly-Me-a-Trainer Option

  • Food and refreshments provided for corporate teams

Do You Want a Customised Training for AWS Data Engineer-Associate (DEA-C01) ?

Get expert assistance in getting your AWS Data Engineer-Associate (DEA-C01) Course customised!

How To Get the AWS Data Engineer-Associate Certification

Here’s a four-step guide to becoming a certified AWS Data Engineer-Associate (DEA-C01) professional.

Do You Want to be a Certified Professional in AWS Data Engineer-Associate (DEA-C01) ?

Join Edoxi’s AWS Data Engineer-Associate (DEA-C01) Course

Why Choose Edoxi for AWS Data Engineer-Associate Course

Edoxi, a leading AWS Data Engineer-Associate Training Institute, provides practical, industry-ready cloud skills aligned with global data engineering standards. Here are the major reasons why professionals and organisations choose us for AWS Data Engineering training

AWS Practical Learning

Our curriculum integrates official AWS best practices with industry-relevant scenarios for comprehensive skill development, building immediately applicable workplace skills.

Industry-Expert Trainers

Learn from AWS professionals with extensive real-world data engineering implementation experience and practical insights from industry projects.

Confidently Pass the Certification Exam

Structured learning, expert guidance, and hands-on practice to ensure success in the AWS certification exam.

Trusted Provider of Corporate Cloud Training

Edoxi provides expert-led AWS and Azure corporate training across government bodies, private firms, and major enterprises throughout the globe.

Complete AWS Learning Pathway

This course connects with other AWS specialisations, creating clear progression opportunities for continued professional development.

Global Training Presence

Edoxi maintains a strong presence across the world's nations, including the GCC countries, African countries, London, Sidney, etc, with successful training delivery.

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Edoxi is Recommended by 95% of our Students

Meet Our Mentor

Our mentors are leaders and experts in their fields. They can challenge and guide you on your road to success!

mentor-image

Manish Rajpal

Manish is a passionate Corporate Trainer, AI Consultant, and Cloud Solutions Architect. He empowers clients across the globe to build and maintain highly available, resilient, scalable, and secure solutions, now with a growing emphasis on AI-powered architectures. With over 15,000 professionals trained, Manish specialises in technologies including Amazon Web Services, Microsoft Azure, Microsoft Copilot and GitHub Copilot and increasingly, AI and Machine Learning.

Manish has led research and workshops focused on integrating AI into cloud environments, exploring use cases like intelligent automation, natural language processing, and responsible AI practices.

Locations Where Edoxi Offers AWS Data Engineer-Associate(DEA-C01) Course

Here are the major international locations where Edoxi offers AWS Data Engineer-Associate(DEA-C01) Course

FAQ

What is the AWS Data Engineer-Associate (DEA-C01) course?

The AWS Data Engineer-Associate (DEA-C01) course at Edoxi prepares you to design, build, monitor, and secure data pipelines on AWS. The training covers the official DEA-C01 exam objectives through practical labs and real-world projects to help you earn the AWS Data Engineer-Associate (DEA-C01) certification.

Is the AWS Data Engineer-Associate (DEA-C01) certification harder than the AWS Solutions Architect Associate (SAA-C03)?

Yes. The AWS Data Engineer-Associate (DEA-C01) certification is more specialised. It focuses on AWS data engineering services, ETL pipelines, data storage, and processing, while SAA-C03 covers broader AWS cloud architecture concepts.

What are the prerequisites for joining the AWS Data Engineer-Associate (DEA-C01) course?
To get the most from Edoxi's AWS Data Engineer-Associate (DEA-C01) course, you should have
 
  • A strong foundation in core IT concepts and technologies.
  • Hands-on experience with Structured Query Language (SQL).
  • Practical experience working with relational databases.
  • A basic understanding of networking concepts.
 

These prerequisites will help you follow the AWS Data Engineer-Associate (DEA-C01) training more effectively and prepare confidently for the AWS Data Engineer-Associate (DEA-C01) certification.

Which certification should I pursue after the AWS Data Engineer-Associate (DEA-C01) certification?
After completing the AWS Data Engineer-Associate (DEA-C01) certification, you can advance to
 
  • AWS Certified Data Analytics – Specialty (DAS-C01)
  • AWS Certified Machine Learning – Specialty (MLS-C01)
  • AWS Certified Solutions Architect – Professional (SAP-C02)
 

Edoxi can help you choose the certification that best matches your career goals.

Is the AWS Data Engineer-Associate (DEA-C01) certification a replacement for AWS Data Analytics – Specialty (DAS-C01)?

No. These certifications serve different purposes. The AWS Data Engineer-Associate (DEA-C01) certification focuses on building and managing data pipelines, while DAS-C01 covers advanced analytics, business intelligence, and data visualisation.  

How does Edoxi prepare me for the AWS Data Engineer-Associate (DEA-C01) certification exam?

Edoxi's AWS Data Engineer-Associate (DEA-C01) training course follows the official exam blueprint. You learn through instructor-led sessions, hands-on AWS labs, practice exercises, and real-world projects to build the skills needed to pass the certification exam confidently. 

What is the difference between a Data Engineer and a Data Scientist?
A Data Engineer builds data pipelines, manages data infrastructure, and prepares data for analysis. A Data Scientist uses that data to build predictive models and generate business insights. Edoxi's AWS Data Engineer-Associate (DEA-C01) training focuses on the engineering side of data.
How long does the AWS Data Engineer-Associate (DEA-C01) course take?
The AWS Data Engineer-Associate (DEA-C01) course includes 40 hours of training. Edoxi offers weekday, weekend, and corporate schedules to suit different learning needs.
Will I get hands-on experience during the AWS Data Engineer-Associate (DEA-C01) training?
Yes. Edoxi provides hands-on lab sessions using real AWS services. During the AWS Data Engineer-Associate (DEA-C01) training, you work on practical projects using AWS data engineering tools.
Can Edoxi provide corporate AWS Data Engineer-Associate (DEA-C01) training?
Yes. Edoxi offers customised AWS Data Engineer-Associate (DEA-C01) training for organisations. The course can be tailored to your team's learning objectives and delivered online or onsite.
Which AWS services will I learn in the AWS Data Engineer-Associate (DEA-C01) course?
The AWS Data Engineer-Associate (DEA-C01) Training course covers major AWS data services, including Amazon S3, AWS Glue, Amazon Redshift, Amazon Kinesis, Amazon EMR, AWS Lambda, Amazon Athena, and Amazon QuickSight.
Who should join the AWS Data Engineer-Associate (DEA-C01) Certification classes?

Edoxi's AWS Data Engineer-Associate (DEA-C01) Certification classes are ideal for data engineers, cloud engineers, ETL developers, database professionals, software developers, and anyone planning a career in AWS data engineering.

What career opportunities are available after completing the AWS Data Engineer-Associate (DEA-C01) certification?

After earning the AWS Data Engineer-Associate (DEA-C01) certification, you can apply for roles such as AWS Data Engineer, Cloud Data Engineer, ETL Developer, Data Platform Engineer, Big Data Engineer, and Data Pipeline Engineer across various industries.

What is the average salary after earning the AWS Data Engineer-Associate (DEA-C01) certification?

The average salary for an AWS Data Engineer is approximately USD 130,000 per year globally. Completing Edoxi's AWS Data Engineer-Associate (DEA-C01) training course helps you develop the skills needed to pursue high-paying AWS data engineering roles. 

Which related AWS certification courses can I take at Edoxi?

Edoxi also offers several AWS certification programmes to help you expand your cloud expertise, including

  • AWS Certified Cloud Practitioner (CLF-C02) for cloud fundamentals.
  • AWS Solutions Architect – Associate (SAA-C03) for AWS architecture and solution design.
  • AWS Certified DevOps Engineer – Professional (DOP-C02) for advanced DevOps automation and operations on AWS.

These courses complement the AWS Data Engineer-Associate (DEA-C01) certification and support long-term career growth in cloud computing.