Data Engineering
Build cloud data pipelines with SQL, Python, Snowflake, dbt, PySpark and Airflow.
- Duration
- 12 or 24 weeks
- Classes
- Live online
- Learner rating
- 4.6/5
- Format
- Modern Analytics Engineering & Enterprise Big Data / Cloud Engineering
Our learners work at
Who is this for?
- College students in their 1st, 2nd, 3rd or 4th year
- Recent graduates starting a career in tech
- Anyone moving into tech from another career
- Working professionals who want to add AI, data or full stack skills to their current role
- Developers who want to move from using AI to building it
What will you learn?
- SQL
- Python
- Snowflake
- dbt
- Databricks
- PySpark
- AWS S3
- Apache Airflow
Roles you can aim for
- Junior Data Engineer
- Big Data Engineer
- Analytics Engineer
- Cloud Data Engineer
What makes this program different
- Production-Grade Portfolio: Build and deploy an entire end-to-end cloud data ecosystem hosted live on GitHub.
- Modern Tech Stack Mastery: Gain hands-on operational experience with SQL, Python, Snowflake, dbt, Databricks, PySpark, AWS S3, and Apache Airflow.
- Real-World Engineering: Solve actual enterprise challenges involving multi-source data extraction, relational modeling, and distributed cloud processing.
- Career Acceleration: Position yourself strongly for high-demand roles such as Junior Data Engineer, Analytics Engineer, and Cloud Data Engineer.
Curriculum and projects
Choose your track
| Month | Focus | Outcome |
|---|---|---|
| Month 1 | Core & Advanced SQL Analytics | Complex SQL joins, CTEs, Window functions, and query performance optimization |
| Month 2 | Python Core, APIs & Data Wrangling | Robust Python ingestion scripts, REST API parsers, and Pandas data cleaners |
| Month 3 | Data Modeling, Snowflake, dbt & First Capstone | Star schema models, dbt transformation layers, and Automated Analytics Pipeline |
Month 1
- Focus
- Core & Advanced SQL Analytics
- Outcome
- Complex SQL joins, CTEs, Window functions, and query performance optimization
Month 2
- Focus
- Python Core, APIs & Data Wrangling
- Outcome
- Robust Python ingestion scripts, REST API parsers, and Pandas data cleaners
Month 3
- Focus
- Data Modeling, Snowflake, dbt & First Capstone
- Outcome
- Star schema models, dbt transformation layers, and Automated Analytics Pipeline
Projects and capstones
First Half Capstone
- Automated Analytics Pipeline
| Month | Focus | Outcome |
|---|---|---|
| Month 1 | Core & Advanced SQL Analytics | Complex SQL joins, CTEs, Window functions, and query performance optimization |
| Month 2 | Python Core, APIs & Data Wrangling | Robust Python ingestion scripts, REST API parsers, and Pandas data cleaners |
| Month 3 | Data Modeling, Snowflake, dbt & First Capstone | Star schema models, dbt transformation layers, and Automated Analytics Pipeline |
| Month 4 | Big Data & PySpark Fundamentals | Databricks clusters, PySpark DataFrames, nested JSON parsing, and OOM tuning |
| Month 5 | AWS Cloud Infrastructure & Apache Airflow | AWS S3 storage integration, Airflow DAGs, and automated task orchestration |
| Month 6 | Lakehouse Architecture, Version Control & Final Capstone | Medallion architecture (Bronze-Silver-Gold), Git versioning, and Enterprise Cloud Lakehouse |
Month 1
- Focus
- Core & Advanced SQL Analytics
- Outcome
- Complex SQL joins, CTEs, Window functions, and query performance optimization
Month 2
- Focus
- Python Core, APIs & Data Wrangling
- Outcome
- Robust Python ingestion scripts, REST API parsers, and Pandas data cleaners
Month 3
- Focus
- Data Modeling, Snowflake, dbt & First Capstone
- Outcome
- Star schema models, dbt transformation layers, and Automated Analytics Pipeline
Month 4
- Focus
- Big Data & PySpark Fundamentals
- Outcome
- Databricks clusters, PySpark DataFrames, nested JSON parsing, and OOM tuning
Month 5
- Focus
- AWS Cloud Infrastructure & Apache Airflow
- Outcome
- AWS S3 storage integration, Airflow DAGs, and automated task orchestration
Month 6
- Focus
- Lakehouse Architecture, Version Control & Final Capstone
- Outcome
- Medallion architecture (Bronze-Silver-Gold), Git versioning, and Enterprise Cloud Lakehouse
Projects and capstones
First Half Capstone
- Automated Analytics Pipeline
Final Capstone
- The Enterprise Cloud Lakehouse
Fees and enrollment
12 Weeks Foundations
12 weeks (3 months)
- Program fee
- ₹50,000
- Early bird offer
- – ₹15,000
- You pay
- ₹35,000
24 Weeks Advanced
24 weeks (6 months)
- Program fee
- ₹70,000
- Early bird offer
- – ₹21,000
- You pay
- ₹49,000
Advanced 3 months
Already finished 12 Weeks Foundations? Continue with the advanced half of the program.
- Program fee
- ₹50,000
- Early bird offer
- – ₹15,000
- You pay
- ₹35,000
Save ₹21,000 with 24 Weeks Advanced
Foundations and Advanced bought separately cost ₹70,000. The full 24 weeks costs ₹49,000, so you save ₹21,000.
Common questions
How much do the programs cost?
Each program page shows the Program fee, the Early bird offer and the amount You pay.
What payment options are available?
You can pay through UPI, and EMI options are also available. After you click Enroll now, our team shares the payment details with you on WhatsApp.
How do I enroll?
Choose your program and track, then click Enroll now. Share your name, phone number and email, and continue on WhatsApp, where our team shares the payment details and the next steps.
What is your refund policy?
If you cancel within 7 days of your cohort's start date, you receive a pro-rata refund. Please read our Refund & Cancellation Policy for the full details.
Can I move to a later batch?
Yes. You can transfer to a later batch once.
See a class before you decide
Join the free demo for this program on Saturday at 7:00 PM (IST).
From ₹35,000
View fees