Advanced Internship on Building ETL Pipelines on AWS
Master building production-grade ETL pipelines on AWS with Python, Spark, and key AWS services. Become job-ready in 1 month with hands-on projects and expert mentorship.
About This Course
This 1-month advanced internship program focuses on building ETL pipelines on AWS. Unlike conventional training providers, this program emphasizes hands-on learning, professional readiness, and real-world project execution. By the end, participants will be capable of designing, building, and deploying production-grade ETL pipelines using a comprehensive suite of AWS services.
What You Will Learn
Hands-on Projects
Apply your learning through real-world projects that build your portfolio and showcase your skills
Unique method to make you professionally rich
Progress through our comprehensive program which makes qualified professional to earn their awards
Bronze Award
Begin your journey with foundational skills and basic certification.
Course Curriculum
Technologies You Will Learn
Master the most in-demand tools and technologies for data analytics
AWS Services (Glue, S3, Redshift, Lambda, Kinesis, Step Functions, CloudWatch, DynamoDB)
Python
SQL
Apache Spark
Pandas
Git & GitHub
AWS CodePipeline
AWS CodeBuild
What Our Students Say
Hear from our students who have transformed their careers with our courses
Why Choose Edjamon?
Discover the difference between Edjamon and traditional learning platforms
| Features & Criteria | EdJAMON | Other Platforms |
|---|---|---|
Duration | 1 Month (intensive, project-focused, job-ready) | 4–6 Months (longer, less focused, often theory-heavy) |
Learning Format | Live Classes + Mentor Support + Real Projects + Code Reviews | Mostly self-paced, recorded videos |
Core Skills & Languages | Python + SQL + PySpark (hands-on from Day 1) | Often limited to SQL basics or only theoretical coverage |
AWS Services | Glue, S3, Redshift, Lambda, Kinesis, Step Functions, DynamoDB, CloudWatch | Covers only a subset (commonly S3 + Redshift, Glue basics) |
ETL Pipeline Development | Batch + Real-time pipelines, automation with Lambda, orchestration with Step Functions | Typically batch-only, little/no real-time focus |
Version Control & CI/CD | Git/GitHub + AWS CodePipeline + CodeBuild | Rarely covered, deployments manual or skipped |
Capstone Project | End-to-end ETL pipeline (Batch + Real-time) deployed on AWS | Case studies or toy datasets only |
Mentorship & Code Reviews | Weekly reviews, 1:1 mentoring, professional practices | Very limited or none |
Career & Placement Support | Portfolio projects, GitHub-ready code, mock interviews, resume prep | No structured support |
Job Roles After Program
Explore exciting career opportunities after completing this program
Data Engineer
ETL Developer
Cloud Data Engineer
Big Data Engineer
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Frequently Asked Questions
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