AWS Data Engineering + AgenticAI MasterClass on 📅 3rd July @ 8:30 PM IST
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🔥 FREE Live Masterclass

Master AWS Data Engineering + AgenticAI

How to crack a 10LPA to 60LPA job

Practical roadmap to high-paying AWS Data Engineering roles and add AgenticAI skills employers want.

60 Days Action Plan Week-by-week roadmap
Real Project Strategy Portfolio-first execution
AgenticAI for Data Engineers Practical add-ons
2-Hour Free Masterclass Recruiter-ready profile

Mentor - Velmurugan M.S

Data Architect | Ex-IBM, Cognizant & HP | 17+ years experience

Starts On 3rd July 2026
(08:30 PM)

Language - English

Fill Out The Form Now!
Bonus: You’ll also get a checklist for “Job-ready AWS portfolio” + interview prep tracker.

Success Stories

Badal

Ayushi

( Hexaware Technology )

Old Package:

20 L

New Package:

26 L

Ritu

Pritesh

( Mckinsey,lti mindtree,SteerLean )

Old Package:

15 L

New Package:

30 L

WHAT YOU LEARN

6-phase AWS Data Engineering roadmap covering infrastructure, compute, IaC, Spark, tuning, and analytics.

Phase 1: Core Infrastructure

  • Configure IAM roles and security policies
  • Setup S3 buckets and CLI environments
  • Master serverless and cloud basics

Phase 2: Compute & Databases

  • Build with Lambda and Step Functions
  • Integrate RDS (SQL) and DynamoDB (NoSQL)
  • Automate triggers using EventBridge

Phase 3: Infrastructure as Code

  • Provision resources using Terraform
  • Script AWS actions with boto3
  • Deploy via GitHub CI/CD pipelines

Phase 4: Data Lake & Spark

  • Catalog data with AWS Glue and Athena
  • Process big data using PySpark DataFrames
  • Manage incremental loads and bookmarks

Phase 5: Architecture & Tuning

  • Build Medallion (Bronze/Silver/Gold) layers
  • Optimize Spark joins and handle data skew
  • Implement Apache Iceberg for lakehouses

Phase 6: Warehousing & Analytics

  • Integrate Snowflake and Redshift clusters
  • Manage JSON/Variant semi-structured data
  • Execute Snowpark bulk loads and Time Travel

Offer Letters

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Reviews

Vishal Yennam avatar

Soumya Parida

LinkedIn
★★★★★

Velmurugan is a very nice tutor and very well equipped with bigdata technologies like Hadoop, python, pyspark, sql, AWS and azure services. Previously I was into support environment,but with his help I transitioned my career into data engineering domain with a decent salary hike. He not only cleared the concepts but also used to give me realtime scenarios which helped me a lot in cracking the interviews. So would highly recommend everyone to attend his training who want to transition their career in data engineering domain.

Abhishek Sharma avatar

Paramjit Singh

LinkedIn
★★★★★

Velmurugan sir ability to break down complex concepts into simpler, easy-to-understand explanations is remarkable. He guided me step by step, ensuring I had a solid grasp of both foundational and advanced topics. His mentorship was instrumental in helping me clear the Databricks certification, which had been a major goal for me.

Tejaswi S avatar

Kirti Sharma

Google
★★★★★

Learning from Velmurugan was an incredible experience. His deep knowledge of AWS Glue, Spark, and Databricks is matched by his ability to teach in a way that makes even the most complex topics approachable. I’m extremely grateful for his mentorship and would highly recommend him to anyone aspiring to grow in the fields of data engineering or cloud technologies. Velmurugan’s commitment to his students' success truly sets him apart.

About the Mentor

🎓 AWS Certified

Data Architect | Ex-IBM, Cognizant & HP | 17+ years experience

Velmurugan has 17+ years of industry experience and has worked at global giants like IBM, HP, and Cognizant,

Velmurugan M.S. is a veteran Data Architect now channeling his deep technical mastery into the field of specialized education. He brings 9+ years of dedicated expertise in Big Data technologies—specifically Apache Spark, Databricks, and Snowflake—to the classroom, offering students a bridge between academic theory and production-grade engineering.
As an educator, Velmurugan’s "practitioner-first" approach is his greatest asset. He doesn't just teach ETL; he teaches the art of designing scalable Lakehouse architectures and high-performance ELT processes that survive real world stress tests. His recent work integrating agentic AI using AWS Bedrock and LangGraph ensures his curriculum remains at the cutting edge of the AI-driven data revolution.

60 LPAHighest CTC Recorded
2000+ LearnerFrom 30+ Countries
1000+ HoursTraining
200+ CareerTransformation
100+ BatchesDelivered

Who Is This Workshop For?

New to AWS
Basic knowledge of Python Or SQL
Learn from Industry Expert
Prefers interactive learning
Desires practical experience

Certification

Certificate Preview

How certification works :

  • Attend the live masterclass session.
  • Complete the required roadmap steps/project checklist.
  • Submit final details and get your completion certificate.

Some of the tools you will learn in this masterclass

AWSAWS
Apache SparkApache Spark
Amazon RDSAmazon RDS
Amazon S3Amazon S3
AWS GlueAWS Glue

Frequently Asked Questions (FAQs)

  • If you’re working in Support, Testing, Development, .NET, SQL, Power BI, Informatica, SSIS, or Mainframe — this masterclass is your bridge to AWS Data Engineering.
  • No prior AWS experience? No problem. We cover everything from basics to advanced, to make you industry-ready.
  • Even non-tech learners can join the program.
  • Data Integration: Design real‑world ETL pipelines using AWS Glue, Step Functions, and Amazon Managed Airflow to move data across RDS, DynamoDB, S3, and Iceberg/Snowflake/Redshift.​
  • Big Data & Compute: Build scalable PySpark workloads on AWS Glue and EMR, applying Medallion architecture and Spark optimization best practices.
  • Storage & Analytics: Implement S3‑based data lakes, Apache Iceberg tables, Amazon Redshift Serverless, Snowflake on AWS, and Athena for end‑to‑end analytics.
  • SQL Fundamentals: Strengthen SQL on Athena, Redshift, Snowflake, and RDS with real scenarios like CTEs, SCD Type 2, and incremental data loads.
  • Our program is designed to bridge the gap between learning and earning.
  • The Blueprint: Master the tools and FAQs across the full stack—AWS, Pyspark, and Snowflake.
  • The Portfolio: Build a high-impact project portfolio to prove your technical expertise.
  • The Personal Brand: Optimise LinkedIn and Resume to ensure you stand out to top-tier recruiters.
  • The Rehearsal: Gain confidence through mock interviews to crack high-paying AWS Data Engineering roles
  • 60 Days.
  • By balancing technical depth with practical mentorship, we ensure you gain maximum proficiency in minimum time. Your transition to AWS Data Engineering isn't a years-long process—it's a 60-day strategic shift.

Ready to join?

Click below to register. After successful registration you’ll be redirected to WhatsApp group.