Live online · 90 hours · Beginner to Advanced
AWS Data Engineering Course — 9 Weeks across Glue, EMR, Redshift, Kinesis and MWAA
Nine structured weeks from PySpark foundations to production AWS pipelines — Glue, Lambda, Step Functions, EMR, Redshift, MSK/Kinesis, Airflow and Databricks.
What you will be able to do
- Design a lakehouse on S3 with Glue Catalog, Lake Formation permissions and Iceberg tables
- Build ETL with Glue (Spark and Python shell), EMR Serverless and Step Functions
- Model and tune Redshift: distribution and sort keys, RA3, Serverless, Spectrum, materialised views
- Stream with Kinesis Data Streams, Firehose, MSK (Kafka) and Flink/Managed Service for Apache Flink
- Orchestrate with Amazon MWAA (Airflow) and monitor cost with CUR + Cost Explorer
- Pass AWS Certified Data Engineer – Associate
Curriculum — 9 weeks · 50 weekday sessions + 9 weekend workshops · 5 major projects
Sessions run live; every session is recorded. Labs are hands-on from week one.
- PySpark Introduction & Spark Architecture
- Databricks Introduction
- PySpark Built-in Functions
- Window Functions
- Data Cleaning with PySpark
- Weekend lab: Claude Code + Prompt Engineering for Data Engineers
- spark-submit Internals
- JSON Processing
- JDBC Data Processing
- XML, CSV and Pandas Integration
- Parquet, ORC, Avro, Delta & Iceberg
- Weekend lab: File-Format & Performance Lab
- AWS Introduction for Data Engineers
- Amazon S3 Deep Dive
- AWS IAM
- EC2 & Amazon RDS for Data Engineers
- AWS Glue Introduction
- Weekend lab: S3 -> Glue Crawler -> Glue PySpark -> S3 Project
- AWS Lambda
- Event-Driven Data Pipelines
- AWS Glue Advanced
- AWS Step Functions
- Monitoring & Logging
- Weekend lab: Event-Driven AWS Data Pipeline
- Databricks + Amazon S3 Integration
- Databricks Utilities
- Delta Lake Advanced
- Medallion Architecture on AWS
- Databricks Performance Optimization
- Weekend lab: Lakehouse Federation + Delta Sharing
- Amazon EMR
- Amazon Redshift Basics
- AWS Lake Formation
- Databricks Asset Bundles (DABs)
- Databricks Lakeflow + Unity Catalog
- Weekend lab: Dev -> Test -> Prod Deployment Lab
- Spark Structured Streaming
- Apache Kafka with Spark
- Amazon MSK
- Amazon Kinesis
- Auto Loader & Streaming Internals
- Weekend lab: AWS Streaming Project
- Apache Airflow Introduction
- Airflow Advanced Orchestration
- Amazon MWAA
- Testing & Observability
- Spark Performance Tuning & RDD Internals
- Weekend lab: Production Troubleshooting Workshop
- Snowflake Fundamentals
- Snowflake Stages & Data Loading
- Snowflake Advanced Overview
- Claude Code for Data Engineers
- Prompt Engineering
- Codex & GitHub Copilot
- Git & GitHub
- GitHub Actions CI/CD
- AWS Data Engineering Architecture
- Interview & Resume Preparation
- Weekend lab: Mock Architecture + Interview Clinic
Hands-on projects
You leave with 5 portfolio projects you can demo in an interview — not toy notebooks.
AWS Batch Data Engineering Pipeline
JDBC ingestion through Glue PySpark into medallion processing, then warehouse publishing with validation.
Event-Driven Serverless Pipeline
Event-driven design on Lambda and Step Functions with retries, failure handling, serverless orchestration and operational monitoring.
AWS Databricks Medallion Lakehouse
Incremental ingestion into Delta Lake on S3 with data-quality rules, Unity Catalog governance and layout optimisation.
Real-Time Streaming Pipeline
Kafka/MSK and Kinesis streaming with checkpointing, late-data handling and streaming transformations.
Metadata-Driven Orchestration
Reusable Airflow framework with dynamic task generation, parameterisation and observability.
Tools and technologies covered
Who this course is for
- Data engineers standardising on AWS
- ETL developers migrating from on-prem
- Cloud engineers adding data skills
- DEA-C01 candidates
Prerequisites
- SQL and basic Python
- No prior AWS experience needed — Week 3 covers AWS, S3 and IAM from zero
- An AWS account (free tier); we show how to set a $20 budget alarm before you touch anything
Frequently asked questions
Labs are designed for the free tier plus a few dollars. We set budget alarms in the first session and every lab ends with a teardown checklist. Expect roughly $15–$40 total across the course if you follow the teardown steps.
No — it is the data specialisation. You'll learn the IAM/VPC/S3 you need, but not EC2 fleet management or hybrid networking in depth.
Both. Week 7 teaches Kafka fundamentals properly (partitions, consumer groups, offsets, compaction, exactly-once) and then applies them on Amazon MSK, alongside Kinesis for comparison.
AWS Certified Data Engineer – Associate (DEA-C01). Note that the older Data Analytics – Specialty (DAS-C01) has been retired — do not buy prep material for it.
A new batch starts every Friday. You pick one of three daily slots — 6:00–7:30 AM IST, 7:30–9:00 AM IST or 7:00–8:30 PM IST — and classes then run Monday to Friday in that slot. In US Eastern time the two morning slots start at 8:30 PM and 10:00 PM the previous evening and the evening slot at 9:30 AM the same day (EDT, mid-March to early November); each is one hour earlier in winter (EST: 7:30 PM, 9:00 PM and 8:30 AM). A weekend (Saturday and Sunday) batch runs as well.
Upcoming batches
A new batch starts every Friday
Pick a start date, then one of three daily slots. Classes run Monday to Friday, live and instructor-led on Zoom or Google Meet, capped small and recorded the same day — and you can re-attend any module in a later batch free.
- Next batch
- Upcoming
- Upcoming
- Upcoming
Morning batch 1 · Mon–Fri
6:00 – 7:30 AM IST
US Eastern 8:30 – 10:00 PM EDT Sun–Thu
Next start Fri, Oct 9
Before office hours in India — an evening class for US learners.
Reserve a seat →Morning batch 2 · Mon–Fri
7:30 – 9:00 AM IST
US Eastern 10:00 – 11:30 PM EDT Sun–Thu
Next start Fri, Oct 9
The second morning slot, same curriculum — late evening in the US.
Reserve a seat →Evening batch · Mon–Fri
7:00 – 8:30 PM IST
US Eastern 9:30 – 11:00 AM EDT Mon–Fri
Next start Fri, Oct 9
After work in India — a morning class for US learners.
Reserve a seat →Class times are fixed in IST. US Eastern times are shown for the next start date and move by one hour when US daylight saving time begins or ends.
Need the weekend (Sat & Sun) batch, or not sure which slot fits? WhatsApp +91-9247159150 and we'll hold a seat while you decide.
Venu Katragadda or a course advisor will call or WhatsApp you within one working day with the full syllabus, batch dates and fees. For anything urgent, WhatsApp +91-9247159150.
Free download · PDF
Download the full 90-hour syllabus
Every module, every hour, every lab and all three projects — the same document we hand to corporate clients. No email verification loop; the PDF downloads the moment you submit.
- Every week broken down topic by topic with hours
- All 5 portfolio projects in full
- Prerequisites, tools list and certification mapping
- Fees, EMI options, batch timings and the refund policy
What students say about Venu Katragadda
Verified Google reviews from Sreyobhilashi IT students. Read all 320+ reviews →
“Recently took Databricks classes with Venu to upskill in trending technologies, and the experience exceeded all expectations. While I initially sought guidance only on Databricks, Venu provided in-depth training across the entire ecosystem.”
Databricks · Cleared DE Professional Cert · Verified Google review
“I recently completed the Data Engineering course on Databricks and AWS. Venu Sir delivers instruction at the next level, focusing on high-performance learning. He explains every concept clearly and thoroughly, accompanied by practical examples.”
Databricks & AWS Training · Verified Google review
“I had a truly valuable experience with Venu's Spark training along with AWS & Azure Databricks Training. He is highly knowledgeable, and the sessions are very well structured with extensive hands-on coverage.”
AWS & Azure Databricks Training · Verified Google review
Foundation course or masterclass?
We run two tiers. Most people should start with the foundation course on our sister site and step up later — this page is the advanced one.
Foundation · databrickstraining.in
AWS Data Engineering Training
₹22,000
- 70 hours of live instruction
- Covers the job-ready core of the stack
- Best if you are new to the platform or changing careers
- Same trainer, same teaching style
Masterclass · this page
AWS Data Engineering Masterclass
₹28,000
- 90 hours — roughly 25–30 extra hours of depth
- Internals, performance tuning and cost engineering modules
- Three reviewed portfolio projects instead of guided labs
- Architecture review and certification drill included
- Best if you already work with the stack and want senior-level depth
Not sure which fits? WhatsApp +91-9247159150 and Venu Katragadda will tell you straight — including when the cheaper one is the right answer.
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