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AWS Data Engineer Course
Data Engineering

AWS Data Engineer Course

Join our AWS Data Engineer Course and AWS Data Engineer Certification Training to learn cloud data engineering, AWS data pipelines, and practical data management skills. This AWS Data Engineer Training helps beginners and professionals prepare for AWS certification and career opportunities.

5/5(4,890 Reviews)

Level

Advanced

Duration

8 Weeks

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About AWS Data Engineer Course

TechPratham’s AWS Data Engineer Course is designed for learners seeking practical skills in Amazon Web Services data engineering. This AWS Data Engineering Course covers cloud data pipelines, data ingestion, transformation, storage, and processing using AWS data services.

The AWS Data Engineer Training focuses on building, managing, and monitoring scalable data solutions through hands-on exercises and real-world projects. This AWS Data Engineer Online Course is suitable for beginners, freshers, and working professionals looking to develop industry-relevant cloud data engineering skills.

Whether you are exploring an AWS Data Engineer Course for Beginners or preparing through AWS Data Engineer Certification Training, the program supports learning aligned with the AWS Certified Data Engineer Associate credential. Learners can also explore AWS Data Engineer Certification Cost and exam requirements before pursuing certification.

The course combines practical training with certification-focused learning to help learners prepare for AWS data engineering roles. For learners seeking career support, the AWS Data Engineer Course with Placement can provide guidance and placement assistance, subject to the program’s actual offerings.

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Training Plan

01
About trainer

About trainer

Working professional who is carrying more than 10 years of industry experience.

02
Decks & Updated Content

Decks & Updated Content

Access to updated presentation decks shared during live training sessions.

03
e-Book

e-Book

E-book provided by TechPratham. All rights reserved.

04
Assignments & MCQs

Assignments & MCQs

Module-wise assignments and MCQs provided for practice.

05
Video Recording

Video Recording

Daily Session would be recorded and shared to the candidate.

06
Projects

Projects

Live projects will be provided for hands-on practice.

07
Resume Building

Resume Building

Expert-guided resume building with industry-focused content support.

08
Interview Preparation

Interview Preparation

Comprehensive interview preparation with real-time scenario practice.

AWS Data Engineer Course Curriculum

Module 1: AWS Data Engineering Fundamentals

Understand AWS cloud infrastructure, data engineering architecture, core services, and the foundations of building cloud-based data solutions.

Introduction to AWS Data Engineering
AWS Global Infrastructure and Regions
AWS Console and Account Fundamentals
AWS Data Engineering Architecture
Data Engineering Lifecycle
AWS Shared Responsibility Model

Module 2: SQL and Data Engineering Fundamentals

Develop SQL and data modeling skills required for data ingestion, transformation, analytics, and warehouse development on AWS.

SQL Fundamentals and Advanced Queries
Joins, Subqueries, and Common Table Expressions
Window Functions and Aggregations
Relational Data Modeling
Normalization and Denormalization
Query Optimization Fundamentals

Module 3: Amazon S3 and Data Lake Architecture

Learn to build scalable cloud data lakes using Amazon S3, including storage organization, data formats, security, and lifecycle management.

Amazon S3 Buckets and Objects
Data Lake Architecture
Partitioning and Folder Structures
CSV, JSON, Parquet, and ORC Formats
S3 Versioning and Lifecycle Policies
S3 Encryption and Access Management

Module 4: AWS Glue and ETL Development

Build ETL pipelines using AWS Glue for extracting, transforming, and loading data from multiple sources into analytical storage systems.

AWS Glue Architecture
Glue Crawlers and Data Catalog
Glue Jobs and Job Bookmarks
Glue Studio and Visual ETL
DynamicFrames and DataFrames
Glue Triggers and Workflow Management

Module 5: PySpark and Distributed Processing

Develop distributed data processing skills with Python and PySpark for transforming large datasets in AWS environments.

Python for Data Engineering
PySpark Fundamentals
DataFrames and Spark SQL
Data Transformation and Aggregation
Joins, Partitioning, and Shuffling
Spark Performance Optimization

Module 6: Amazon Redshift and Data Warehousing

Understand cloud data warehousing and learn to design, load, query, and optimize analytical datasets using Amazon Redshift.

Amazon Redshift Architecture
Data Warehouse Fundamentals
Redshift Tables and Schemas
Data Loading with COPY
Distribution Styles and Sort Keys
Query Performance and Workload Management

Module 7: Amazon Athena and Data Analytics

Query data directly from Amazon S3 using Amazon Athena and develop efficient analytical workflows for cloud data lakes.

Amazon Athena Fundamentals
Athena and AWS Glue Data Catalog
External Tables and Partitioning
SQL Queries on S3 Data
Query Cost Optimization
Athena Integration with Data Lakes

Module 8: AWS Lambda and Serverless Data Processing

Build event-driven data processing workflows using AWS Lambda and integrate serverless functions with AWS storage and data services.

AWS Lambda Fundamentals
Event-Driven Architecture
S3 Event Notifications
Lambda and AWS Glue Integration
Error Handling and Retries
Serverless Data Pipeline Design

Module 9: AWS Step Functions and Orchestration

Orchestrate multi-step data workflows using AWS Step Functions and coordinate data ingestion, transformation, validation, and processing tasks.

Step Functions Fundamentals
State Machines and Workflow States
AWS Glue Job Orchestration
Lambda and Step Functions Integration
Retry and Error Handling
Workflow Monitoring and Recovery

Module 10: Amazon Kinesis and Streaming Data

Develop real-time data processing pipelines using Amazon Kinesis and understand streaming ingestion, event processing, and monitoring.

Streaming Data Fundamentals
Amazon Kinesis Data Streams
Kinesis Data Firehose
Real-Time Data Ingestion
Stream Processing and Consumer Applications
Monitoring Streaming Pipelines

Module 11: AWS Data Security, Governance, and Operations

Secure AWS data platforms and maintain reliable pipelines through access control, monitoring, data quality, and operational best practices.

AWS IAM and Least-Privilege Access
AWS KMS and Encryption
AWS Lake Formation Fundamentals
AWS CloudTrail and CloudWatch
Data Quality and Validation
Data Pipeline Troubleshooting
Cost and Performance Optimization

Module 12: Capstone Projects and Certification Preparation

Apply AWS data engineering concepts through end-to-end projects and prepare for the AWS Certified Data Engineer – Associate examination.

End-to-End ETL Pipeline Development
AWS Data Lake Project
Cloud Data Warehouse Project
Streaming Data Pipeline Project
Project Documentation and Deployment
DEA-C01 Exam Domain Revision
Practice Questions and Mock Assessments
Interview and Career Preparation

Data Engineering Courses

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Additional Program Highlights

Learning Materials

Comprehensive study materials and resources

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Resume Writing

Professional resume building session

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Interview Preparation

Master your interview skills

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Live Project Demo

Real-world project demonstrations

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Upcoming Batches

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Who Should Take AWS Data Engineer Course?

IT Professionals

Non-IT Career Switchers

Fresh Graduates

Career Opportunities After Learning AWS Data Engineering

AWS Data Engineer

Cloud Data Engineer

AWS Data Pipeline Engineer

Key Projects

AWS Data Engineer Course

Saint-Gobain

Saint-Gobain – AWS Data Lake Pipeline

Scenario: Design a cloud data lake for a manufacturing analytics scenario using Amazon S3 to organize production, quality, and operational datasets.

Live Work:

  • Build S3 data lake storage and partitions.
  • Create Glue ETL jobs for data transformation.
  • Catalog datasets for analytics with Athena.
Outcome: Develop a scalable manufacturing data lake.
Metro Bank

Metro Bank – AWS Customer Data ETL

Scenario: Develop a secure customer data pipeline for a banking analytics scenario using AWS ingestion, transformation, storage, and access-control services.

Live Work:

  • Ingest customer records into Amazon S3.
  • Transform and validate data with AWS Glue.
  • Apply IAM access and encryption controls.
Outcome: Build a secure customer data pipeline.
WNS

WNS – AWS Service Analytics

Scenario: Build an analytics pipeline for service operations using AWS data services to process operational records and prepare reporting datasets.

Live Work:

  • Store operational records in Amazon S3.
  • Load transformed datasets into Redshift.
  • Query and analyze data using SQL.
Outcome: Create analytics-ready service datasets.
NovaTech Solutions

NovaTech Solutions – AWS Operations Streaming

Scenario: Develop a streaming data solution for operational events, combining real-time ingestion, event processing, and analytical storage on AWS.

Live Work:

  • Ingest events using Amazon Kinesis.
  • Process events with Lambda functions.
  • Monitor and validate pipeline execution.
Outcome: Deliver a real-time operations pipeline.
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Our Success Mantra

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Commitment

  • Ensuring quality training every day

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Fulfillment

  • Meeting learning goals with confidence

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Accomplishment

  • Students achieving industry-ready expertise

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Additional Support We Provide

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Alumni Sessions

Interview Preparation

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What is an AWS Data Engineer Course?

Who can enroll in AWS Data Engineer Training?

What is the syllabus of an AWS Data Engineer Course?

Is AWS Data Engineering suitable for beginners?

What are the prerequisites for AWS Data Engineer Training?

Which AWS services are used in data engineering?

What is the role of an AWS Data Engineer?

What is AWS Glue?

What is the difference between Amazon S3 and Amazon Redshift?

What is the AWS Glue Data Catalog?

What is the difference between AWS Glue and Amazon EMR?

What is Amazon Athena?

AWS Certified Data Engineer

The AWS Certified Data Engineer – Associate is an official professional certification offered by Amazon Web Services (AWS). It validates a candidate’s ability to design, build, secure, operate, and maintain data solutions using AWS services.


Official Certification Details

  • Certification Name: AWS Certified Data Engineer – Associate
  • Exam Code: DEA-C01
  • Certification Provider: Amazon Web Services (AWS)
  • Certification Level: Associate
  • Exam Duration: 130 minutes
  • Exam Questions: 65 questions, including multiple-choice and multiple-response questions
  • Exam Fee: USD 150 (applicable taxes and local pricing may vary)
  • Passing Score: 720 out of 1,000 on the AWS scaled scoring system
  • Certification Validity: 3 years


Official Exam Domains

The DEA-C01 exam covers four major domains:

  1. Data Ingestion and Transformation – 34%
  2. Data Store Management – 26%
  3. Data Operations and Support – 22%
  4. Data Security and Governance – 18%

These domains cover data ingestion, ETL and ELT pipelines, data storage, transformation, data quality, monitoring, troubleshooting, security, access control, and governance using AWS services.


Who Can Take the Exam?

AWS recommends that candidates have approximately 2–3 years of experience in data engineering or data architecture and 1–2 years of hands-on experience with AWS services. These are recommended experience levels, not mandatory formal prerequisites for registering for the exam.


How to Register for the AWS Certification Exam

Candidates can visit the official AWS Certification website, sign in to their AWS Certification account, select AWS Certified Data Engineer – Associate (DEA-C01), and follow the available exam scheduling instructions.


TechPratham Course Completion Certificate

Upon fulfilling the course completion requirements, learners may receive a certificate of completion from TechPratham, subject to the program’s certification policy. This certificate recognizes completion of the TechPratham training program and is separate from the AWS Certified Data Engineer – Associate credential.

The official AWS certification is awarded by Amazon Web Services only to candidates who successfully pass the authorized DEA-C01 certification examination.

Industry-Recognized Certification

Certificate
AWS Data Engineering Certificate

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