Data Engineer Using AWS
The Data Engineer Using AWS training is designed to help learners master cloud-based data engineering solutions using AWS services. It focuses on building end-to-end data pipelines, performing data transformations, managing big data workloads, and automating data workflows. This program is ideal for beginners, working professionals, or those transitioning into data engineering roles in cloud environments.
Days
Course Duration
Year
Placement Support
+
Students Placed
Data Engineering – Detailed Course Content
This course helps you become a proficient AWS Data Engineer by combining core AWS services with real-time projects and hands-on labs. You’ll learn to build ETL pipelines using AWS Glue, process big data using EMR and PySpark, stream real-time data with Kinesis, run SQL queries using Athena, and manage structured/unstructured data across S3, Redshift, and DynamoDB. The training also covers infrastructure automation, cost-effective storage, and secure data handling with IAM and encryption mechanisms.
You’ll gain practical experience by developing data engineering workflows, ingesting large-scale datasets, orchestrating jobs using Step Functions, and analyzing data with QuickSight dashboards.
Tech Stack Covered (With Description):
🔹 AWS Services & Data Tools:
1. Amazon S3 (Data Lake Foundation)
Object storage for structured/unstructured data
Versioning, lifecycle rules, encryption
2. AWS Glue (ETL Platform)
Serverless ETL for data extraction, transformation, and cataloging
Glue Crawlers, Glue Jobs (Python/Spark), Data Catalog
3. Amazon Redshift (Data Warehouse)
Fast, scalable analytics queries
COPY commands, Redshift Spectrum for querying S3
4. Amazon EMR (Big Data Platform)
Hadoop, Hive, Spark clusters for large-scale batch processing
PySpark and notebook-based pipeline development
5. AWS Lambda (Serverless Automation)
Event-driven triggers for ETL tasks and data clean-up
Integration with S3, DynamoDB, Kinesis
6. Amazon Kinesis (Streaming Data)
Real-time ingestion and processing
Integration with Firehose, Lambda, and S3
7. AWS Athena (Serverless SQL Analytics)
Query S3 data directly with ANSI SQL
Partitioned and compressed data access
8. AWS Step Functions (Orchestration)
Manage multi-step workflows and job sequences
Connect Lambda, Glue, and SNS for automated pipelines
9. DynamoDB (NoSQL Storage)
High-performance key-value and document store
Real-time lookups, metadata, or caching layers
10. AWS CloudWatch & CloudTrail
Monitor logs, set alarms, and audit API-level activity
11. AWS QuickSight (Data Visualization)
Create interactive dashboards and charts
Connects with Redshift, Athena, and S3
Tools & Languages:
SQL – Advanced joins, aggregations, and performance tuning
Python – Scripting for Lambda and Glue ETL
PySpark – Distributed data processing on EMR/Glue
AWS CLI & Boto3 SDK – Automation of AWS operations
Jupyter Notebook – PySpark notebook development
Git & GitHub – Version control and collaborative development
Apache Airflow (Optional Advanced Module) – DAG-based pipeline orchestration
Security & Optimization Concepts:
IAM (Role-based access control for services and users)
Data encryption at rest and in transit (SSE-S3, KMS)
Cost optimization with reserved instances and lifecycle policies
Budget alerts and usage monitoring
Job Roles You Can Apply For After completing this course, you’ll be equipped to apply for the following roles in the IT industry:
- AWS Data Engineer
- Cloud Data Engineer
- Big Data Engineer (AWS)
- Data Pipeline Developer
- Redshift Engineer
- ETL Developer – AWS
- AWS Glue Developer
- Data Lake Engineer
- DataOps Engineer
For Freshers (0–1 year experience):
Job Role
- Data Engineer (AWS)
- Junior ETL Developer
Average Salary (INR)
- ₹4.5 LPA – ₹6.5 LPA
- ₹4.0 LPA – ₹6.0 LPA
Top Range (INR)
- Up to ₹7.5 LPA
- Up to ₹7.0 LPA
Mid-Level (1–3 years experience):
Job Role
- AWS Data Engineer
- ETL Developer – Cloud
Average Salary (INR)
- ₹7.0 LPA – ₹10.0 LPA
- ₹6.5 LPA – ₹9.5 LPA
Top Range (INR)
- Up to ₹12.0 LPA
- Up to ₹11 LPA
Senior Level (4+ years experience):
Job Role
- Lead Data Engineer
- Cloud Data Architect
Average Salary (INR)
- ₹13.0 LPA – ₹18.0 LPA
- ₹15.0 LPA – ₹20.0 LPA
Top Range (INR)
- ₹22.0 LPA+
- ₹25.0 LPA+
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