AWS Data Engineer Certification Course (DEA-C01)
AWS Data Engineer Certification Course helps you build practical AWS data engineering skills and prepare for the AWS Certified Data Engineer – Associate (DEA-C01) exam through structured learning, hands-on labs, real data pipeline exercises, projects, and exam-focused preparation.
- Course Fee: ₹24,999
- AWS Exam Fee: Separate
- Training: Instructor-led + hands-on
- Labs: Included
- Projects: Included
- Exam Preparation: Included
- Course Duration: 40 Hours
- Training Mode: Online / Offline
What Is the AWS Data Engineer Certification Course?
The AWS Data Engineer Certification Course is a structured training program that teaches you how to build, operate, secure, and improve data workloads on Amazon Web Services. It focuses on the skills measured in the AWS Certified Data Engineer – Associate (DEA-C01) exam while giving you practical experience with ingestion, transformation, storage, orchestration, monitoring, security, and governance.
AWS Data Engineer Course at a Glance
| Course Detail | Information |
|---|---|
| Course Name | AWS Data Engineer Certification Course |
| Certification | AWS Certified Data Engineer – Associate |
| Exam Code | DEA-C01 |
| Certification Level | Associate |
| Training Provider | Certification Mantra |
| Course Fee | ₹24,999 |
| AWS Exam Fee | Separate |
| Training Type | Instructor-led + Hands-on |
| Labs | Included |
| Projects | Included |
| Exam Preparation | Included |
| Mock Questions | Included |
| Course Duration | 40 Hours |
| Training Mode | Online / Offline |
Important: Certification Mantra provides the training. The official AWS Certified Data Engineer – Associate credential is issued by Amazon Web Services after a candidate passes the DEA-C01 exam.
The certification validates a professional’s ability to work with AWS data services and perform common data engineering tasks across ingestion, transformation, storage, operations, data quality, security, and governance.
Data Pipelines
Understand how data moves from source systems into AWS, through processing layers, and into analytics-ready destinations.
Data Stores
Select and manage AWS storage options based on access pattern, performance, structure, scalability, lifecycle, and cost.
Operations & Governance
Monitor workloads, improve data quality, secure access, and manage metadata, retention, lineage, and governance controls.
Why Learn AWS Data Engineering?
Modern applications generate data from websites, APIs, transaction systems, logs, databases, IoT devices, and streaming platforms. Before analysts or applications can use that data, someone must design a reliable way to collect, clean, transform, store, secure, and deliver it.
AWS provides services for each stage of that lifecycle. This course helps you move beyond isolated service definitions and understand how multiple AWS services work together in a complete data platform.
What Will You Learn?
Ingestion & Transformation
- Batch and streaming ingestion
- ETL and ELT workflows
- AWS Glue and data transformation
- Kinesis streaming patterns
Storage & Analytics
- Amazon S3 data lakes
- Amazon Redshift
- Amazon Athena
- Data partitioning and formats
Operations & Security
- Pipeline orchestration
- Monitoring and troubleshooting
- IAM and encryption
- Data quality and governance
Skills You Will Build
Data Ingestion
Understand how data enters AWS from applications, databases, files, events, APIs, and streaming sources.
Data Transformation
Clean, validate, standardize, enrich, and prepare raw data for downstream analytics and applications.
Pipeline Design
Connect AWS services into repeatable, observable, and resilient workflows.
Storage Design
Choose storage based on data structure, access patterns, performance, durability, scale, and cost.
Security & Governance
Apply IAM, encryption, access controls, metadata, retention, and governance practices.
Performance
Improve performance through partitioning, file formats, query design, and service configuration.
AWS Services and Technologies Covered
Amazon S3AWS GlueGlue Data CatalogAmazon RedshiftAmazon KinesisAmazon EMRAWS LambdaAmazon AthenaAmazon RDSAmazon DynamoDBAWS Step FunctionsAmazon CloudWatchAWS CloudTrailAWS IAMAWS KMSAWS Secrets ManagerAmazon EventBridgeAmazon SNSAmazon SQSAWS DMSSQLPythonApache SparkPySparkJSONCSVParquet
Who Should Take This AWS Data Engineer Course?
Data Professionals
Data Engineers, ETL Developers, SQL Developers, BI Developers, Big Data Engineers, and Data Analysts moving toward engineering.
Cloud & Software Professionals
Cloud Engineers, AWS professionals, developers, database specialists, and data platform engineers.
DEA-C01 Candidates
Professionals who want structured exam preparation supported by hands-on AWS practice and complete workflow understanding.
AWS Data Engineer Certification Prerequisites
There is no need to master every AWS service before starting. Useful foundations include basic SQL, database concepts, tables and schemas, basic programming, cloud concepts, and general awareness of data pipelines.
Python knowledge is useful but does not need to be advanced. The official DEA-C01 exam guide describes the ideal certification candidate as someone with relevant data engineering or data architecture experience plus hands-on AWS experience; this is a target candidate profile, not a mandatory requirement to attend training.
AWS Data Engineer Certification Course Curriculum
The curriculum follows the current DEA-C01 exam-domain structure while keeping implementation and troubleshooting in focus.
Module 1: AWS and Data Engineering Foundations
- Role of a data engineer
- Modern data architecture concepts
- Batch vs streaming
- Structured, semi-structured, and unstructured data
- Data lakes vs data warehouses
- ETL vs ELT
- AWS Regions and Availability Zones
- IAM fundamentals
- Core AWS data services and architecture patterns
Hands-on: Explore the AWS environment, IAM access, and basic storage configuration.
Domain 1: Data Ingestion and Transformation
Module 2: Data Ingestion Architecture
- Batch, streaming, event-driven, file and database ingestion
- Throughput and latency
- Validation and error handling
- Reliable ingestion patterns
Hands-on: Design a workflow that receives source data and lands it in AWS storage.
Module 3: Amazon S3 for Data Engineering
- Buckets and objects
- Prefix strategy
- Storage classes and lifecycle
- Versioning, encryption and access
- Partitioning
- CSV, JSON and Parquet
Hands-on: Build raw, processed and curated data-lake zones.
Module 4: AWS Glue and ETL Processing
- Glue architecture
- Data Catalog and Crawlers
- Glue jobs
- ETL workflows
- Schema changes
- Monitoring and performance
Hands-on: Catalog source data and transform raw records into analytics-ready data.
Module 5: Apache Spark and Data Transformation
- Spark fundamentals and DataFrames
- Filtering, joins and aggregations
- Cleansing and partitioning
- PySpark transformations
- Distributed processing considerations
Module 6: Streaming Data Processing
- Producers and consumers
- Kinesis Data Streams
- Partition keys and shards
- Throughput
- Failure handling
- Real-time architecture
Hands-on: Build a simple streaming pipeline and process incoming events.
Domain 2: Data Store Management
Module 7: Choosing the Right AWS Data Store
- Structured vs unstructured data
- Transactional vs analytical workloads
- Latency, scale, durability and cost
- S3, Redshift, RDS and DynamoDB use cases
Module 8: Amazon Redshift for Data Warehousing
- Architecture
- Loading data
- Table design
- Distribution and sort strategies
- Query performance
- Redshift Spectrum
- Security and monitoring
Hands-on: Load processed data and run analytical SQL queries.
Module 9: Amazon Athena and Serverless Querying
- Athena architecture
- Glue Data Catalog integration
- Partitioning
- Parquet querying
- Cost-aware query design
Hands-on: Query a partitioned S3 dataset.
Module 10: Database and Data Lifecycle Management
- Retention and archival
- Backup and recovery
- Replication
- Schema evolution
- Versioning
- Storage optimization
Domain 3: Data Operations and Support
Module 11: Data Pipeline Orchestration
- Dependencies and sequencing
- Event-driven and scheduled workflows
- Step Functions
- EventBridge
- Lambda automation
- Retries, failures and idempotency
Hands-on: Build a multi-stage workflow that ingests, transforms, validates and stores data.
Module 12: Monitoring and Troubleshooting
- CloudWatch metrics, logs and alarms
- CloudTrail
- Monitoring Glue and Redshift
- Failure analysis
- Permissions and ingestion troubleshooting
Module 13: Data Quality
- Completeness and validity
- Duplicate detection
- Null handling
- Schema validation
- Anomalies
- Failed-record handling
- Reprocessing
Module 14: Performance and Cost Optimization
- Partitioning
- File size and format
- Compression
- Query optimization
- Scaling
- Storage lifecycle and cost-aware architecture
Domain 4: Data Security and Governance
Module 15: AWS Data Security
- IAM users, roles and policies
- Least privilege
- Resource policies
- Encryption at rest and in transit
- KMS
- Secrets Manager
- Auditing access
Hands-on: Configure controlled access to data resources using IAM roles and policies.
Module 16: Data Governance
- Metadata and cataloging
- Ownership and lineage concepts
- Access policies
- Classification
- Retention and auditing
- Sensitive-data management
Hands-On Labs
Lab 1
Create an Amazon S3 data lake structure.
Lab 2
Catalog datasets with AWS Glue Crawlers.
Lab 3
Build a Glue ETL job.
Lab 4
Convert raw CSV data into optimized Parquet.
Lab 5
Query S3 data using Athena.
Lab 6
Load transformed data into Amazon Redshift.
Lab 7
Create a Kinesis streaming workflow.
Lab 8
Trigger data processing using Lambda.
Lab 9
Orchestrate a multi-step workflow.
Lab 10
Configure CloudWatch monitoring and alerts.
Lab 11
Implement IAM permissions for a data pipeline.
Lab 12
Troubleshoot a failed data workflow.
Real-World AWS Data Engineering Projects
Project 1: E-Commerce Batch Data Pipeline
Receive transaction files, store raw data in S3, use Glue for discovery and transformation, optimize the format, load curated data into Redshift, and expose it for analytics.
Skills: S3, Glue, Data Catalog, Redshift, SQL, ETL.
Project 2: Real-Time Event Processing
Build an event flow using Kinesis, processing logic, S3 or Redshift destinations, and monitoring. Practice throughput, streaming design, failure handling, and observability.
Project 3: Serverless Data Processing Workflow
Use S3, Lambda, Step Functions, Glue, and CloudWatch to create an event-driven pipeline without managing traditional servers.
Project 4: Secure Enterprise Data Lake
Design raw, processed, and curated layers with IAM permissions, encryption, lifecycle rules, cataloging, and monitoring.
DEA-C01 Exam Preparation
Use the course labs and mock assessments together with AWS Skill Builder DEA-C01 exam-preparation resources to review official exam topics and practice your readiness.
Understand
Review exam domains, weightings, AWS terminology, question style, and services in scope.
Strengthen
Use labs and revision to close gaps in the topics where your understanding is weak.
Practice
Work through scenario-based questions by identifying requirements, constraints, and the best-fit AWS service.
Assess
Use mock assessments to identify weak areas before scheduling the official exam.
| Exam Detail | Information |
|---|---|
| Certification | AWS Certified Data Engineer – Associate |
| Exam Code | DEA-C01 |
| Level | Associate |
| Duration | 130 minutes |
| Questions | 65 |
| Question Types | Multiple Choice and Multiple Response |
| Official Exam Price | USD 150 |
| Delivery | Pearson VUE testing center or online proctored |
| Credential Issuer | Amazon Web Services |
Exam information can change. Verify current details on the official AWS Certification page before booking.
DEA-C01 Exam Domains
| Exam Domain | Weight |
|---|---|
| Data Ingestion and Transformation | 34% |
| Data Store Management | 26% |
| Data Operations and Support | 22% |
| Data Security and Governance | 18% |
AWS Data Engineer Certification Cost
Certification Mantra Training Fee
The training fee covers the Certification Mantra learning program.
- Instructor-led sessions
- Labs
- Projects
- Learning material
- Mock questions
- Exam preparation
Official AWS Exam Fee
The official DEA-C01 exam is purchased separately through the AWS certification testing process. Regional/local-currency pricing and taxes may vary.
Exam fee is separate from the ₹24,999 training fee.
How the Training Works
1. Learn the Concept
Start with the problem the AWS service is designed to solve.
2. See the Architecture
Understand where the service fits in a complete data pipeline.
3. Configure It
Work with the service directly in AWS.
4. Test Scenarios
Change inputs, permissions, or processing logic and observe the result.
5. Build Workflows
Connect several services instead of studying each one in isolation.
6. Troubleshoot & Prepare
Diagnose failures and connect practical knowledge to DEA-C01 scenarios.
Certification Mantra Course Certificate vs AWS Certification
Certification Mantra Course Completion Certificate
This confirms completion of the Certification Mantra training program according to the institute’s completion requirements.
AWS Certified Data Engineer – Associate
This is the official AWS credential. To earn it, you must register for and pass the DEA-C01 exam through AWS’s certification testing process.
Important Difference
Completing a Certification Mantra course does not automatically make someone AWS certified. The course is designed to help you prepare for the official exam.
Career Roles Related to AWS Data Engineering
AWS Data EngineerCloud Data EngineerData EngineerETL DeveloperData Platform EngineerBig Data EngineerAnalytics EngineerData Infrastructure Engineer
A certification alone does not guarantee employment. Employers may also evaluate SQL, programming, data modeling, cloud experience, projects, troubleshooting ability, communication, and previous experience.
Why Choose Certification Mantra?
Understand
Learn why AWS services are used rather than memorizing isolated definitions.
Build
Apply concepts through labs, connected workflows, and practical data engineering projects.
Prepare
Map practical understanding to the four DEA-C01 exam domains and scenario-based questions.
Learning path: Ingest → Store → Transform → Orchestrate → Monitor → Secure → Govern
Related Certification Mantra Resources
Browse certification training programs
Explore another AWS certification path
Ask about batches, trainer, fees, and delivery details
What Our Students Say About Certification Mantra
These are general Certification Mantra learner testimonials from our homepage, not reviews specific to the AWS Data Engineer course.
The learner appreciated the informative classes, discussions, and assignments, and said the overall training experience helped build useful practical understanding.
The learner highlighted the well-organized material, easy-to-follow presentation, knowledgeable instructors, and the opportunity to ask questions during training.
The learner described the training as practical and confidence-building, with useful guidance that supported preparation for real professional situations.
Certification Mantra Address & Map
Join the AWS Data Engineer course in Hyderabad at our classroom near JNTU, Hyder Nagar, or attend the same training live online.
Certification Mantra
Metro Pillar No: A689, Metro Station,
3rd Floor, Dr Atmaram Estates,
beside Sri Bhramaramba Theatre near JNTU,
Hyder Nagar, Vasantha Nagar,
Hyderabad, Telangana 500072.
Phone: +91 9704179997
AWS Data Engineer Certification Course FAQs
1. What is the AWS Data Engineer Certification Course?
It is a training program focused on AWS data engineering skills and preparation for the AWS Certified Data Engineer – Associate DEA-C01 exam. The course covers ingestion, transformation, storage, operations, security, governance, labs, projects, and exam-focused practice.
2. What is DEA-C01?
DEA-C01 is the exam code for AWS Certified Data Engineer – Associate. It evaluates skills across AWS data pipelines, data stores, operations, transformation, security, and governance.
3. Is AWS Data Engineer Certification suitable for beginners?
Beginners can start learning AWS data engineering, but basic SQL, databases, programming, and cloud concepts make the course easier. Learners without prior AWS experience should allow more time for fundamentals and hands-on practice.
4. What is the AWS Data Engineer certification cost?
AWS currently prices the Associate-level DEA-C01 exam at USD 150. Local-currency pricing and taxes can vary. Certification Mantra’s training fee is separate from the official AWS exam fee.
5. What is the Certification Mantra course fee?
The Certification Mantra course fee is ₹24,999. The official AWS exam fee is separate.
6. What topics are covered in DEA-C01?
The exam focuses on Data Ingestion and Transformation, Data Store Management, Data Operations and Support, and Data Security and Governance.
7. Which AWS services will I learn?
The course covers S3, Glue, Redshift, Kinesis, EMR, Lambda, Athena, RDS, DynamoDB, Step Functions, CloudWatch, IAM, KMS, EventBridge, and related services used in AWS data workflows.
8. Does the course include hands-on labs?
Yes. The course includes practical labs covering ingestion, storage, transformation, querying, orchestration, monitoring, and security.
9. Does the course include projects?
Yes. The program includes AWS data engineering projects involving batch processing, streaming, serverless workflows, and secure data-lake architecture.
10. Does Certification Mantra provide the official AWS certification?
No. Certification Mantra provides training and may issue its own course completion certificate. The official AWS Certified Data Engineer – Associate credential is issued by Amazon Web Services after the candidate passes DEA-C01.
11. Is the AWS exam fee included in the course fee?
No. The ₹24,999 training fee and the official AWS exam fee are separate.
12. How should I prepare for DEA-C01?
Understand the four exam domains, learn the associated AWS services, practice through hands-on labs, build complete data workflows, review weak areas, and use scenario-based questions before attempting mock assessments.
13. Is AWS Data Engineer Certification difficult?
Difficulty depends on experience. Candidates familiar with SQL, data pipelines, AWS, storage, ETL, and data security will generally find the concepts more familiar. New AWS learners should allow more hands-on practice time.
14. Is AWS Certified Data Engineer – Associate worth it?
It can be valuable for professionals working with AWS data platforms or those who want to demonstrate AWS data engineering knowledge. Its value is strongest when supported by practical skills, projects, SQL, and real experience.
15. How long is the DEA-C01 exam?
AWS currently lists the exam duration as 130 minutes.
16. How many questions are in DEA-C01?
AWS currently lists 65 questions using multiple-choice and multiple-response formats.
17. Can I take DEA-C01 online?
AWS currently offers the exam through Pearson VUE, including online-proctored and testing-center options.
18. Does the course teach only exam theory?
No. The course combines exam-domain preparation with labs, architecture discussions, troubleshooting exercises, and end-to-end AWS data engineering projects.
19. Do I need Python for AWS Data Engineering?
Basic programming knowledge is useful. Python is often used in data engineering workflows, automation, transformations, and Spark-based processing, but advanced software-development skills are not required to begin.
20. What should I learn after completing the course?
Depending on your career direction, useful next steps may include deeper SQL, Python, Spark, streaming systems, infrastructure automation, advanced AWS architecture, data governance, or production-grade data platform design.
21. Is the AWS Data Engineer course available in Hyderabad?
Yes. Certification Mantra runs the AWS Data Engineer Certification Course in Hyderabad as classroom training at our centre near JNTU, Hyder Nagar, and also as live online training. Both modes follow the same 40-hour DEA-C01 curriculum with hands-on labs, projects, and exam preparation.
Start Your AWS Data Engineering Journey
Learn how data enters AWS, how it is transformed, where it should be stored, how pipelines are operated, and how information is secured and governed—while preparing for AWS Certified Data Engineer – Associate (DEA-C01).
Course Fee: ₹24,999 • AWS Exam Fee: Separate
