What Makes This Bootcamp Different?
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100% LIVE, instructor-led sessions across 8 weeks. Real-time Q&A, live walk-throughs, and direct doubt-clearing with the faculty.
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Built to make you the end-to-end data person on your team - the one who builds the pipeline, models the data, and ships the report.
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Covers the FULL Modern Data Engineering spectrum, from Advanced SQL and PySpark to Databricks, Microsoft Fabric, dbt, Airflow, Kafka streaming, and CI/CD - the complete production stack.
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Designed and taught by data industry experts & engineering leaders with real-world experience building and shipping production data systems at scale.
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Master the complete modern DE stack: Python, PySpark, Delta Lake, Databricks, Microsoft Fabric, dbt, Airflow, Kafka, ADF, GitHub Actions, Power BI & more.
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Production-first mindset: Spark internals, OPTIMIZE & ZORDER, schema evolution, idempotency, CI/CD, observability - the engineering practices that matter in production data systems.
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Streaming engineering with Kafka, Structured Streaming, watermarking, windowing, and event-time processing - the patterns Indian product teams run today.
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AI-Assisted Data Engineering: Copilot, Cursor, and Claude Code for SQL, dbt, PySpark, and Airflow - the productivity patterns top DE teams are adopting now.
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End-to-end capstone integrating 8 production layers- API ingestion, lakehouse, transformation, orchestration, CI/CD, monitoring, and Power BI. One artefact recruiters read in five minutes.
Hear It From
Our Happy Learners
Our content is rated 4.9/5 from 18458+ Learners
Python
I just finished a SQL course and was really impressed. It did a great job of breaking things down, starting with the basics and gradually moving into more complex stuff like joins and subqueries. The hands-on exercises and real-world examples made it easy to stay engaged and actually learn by doing. Overall, it gave me a solid foundation and I am confident now to apply these skills into real world projects. If you're new to SQL or just want to brush up, I'd definitely recommend it.
Landed a Job
It was a very helpful course that gave me a lot of information and hands-on experience, and I learned a lot about the basics and projects. it will be a good start to a career for anyone. I look forward to enrolling in a few more courses and upskilling myself more.
Thank you.
Landed a Job
As a data analyst stepping into the world of data engineering, I found this course extremely valuable. The concepts were explained in a way that felt approachable, even for someone without a deep engineering background.
Thank you, Dhaval sir, for designing such a practical and insightful course. I especially appreciated how the course bridged the gap between data analysis and engineering — it gave me the confidence to work with pipelines, cloud tools, and data architecture in a structured way. What seemed intimidating at first now feels doable, and I can already see how these skills will strengthen my career.
I’d highly recommend this course to anyone from an analytics background who wants to expand into data engineering without feeling overwhelmed.
I just wanted to take a moment to genuinely appreciate the SQL course by Dhaval Sir on Codebasics. Honestly, learning SQL always felt a little dry and technical to me — but this course completely changed that.
The way Dhaval Sir explains concepts using real-world business problems is just amazing. Instead of just writing queries, you actually think like a data analyst, solving real challenges that companies face. It’s not just about syntax; it’s about understanding how SQL is used in the real world, and that made the whole learning journey so much more interesting and practical.
A huge thanks to Dhaval Sir for creating a course that doesn’t just teach SQL, but makes you actually enjoy learning it. Grateful for the effort and passion you’ve put into this course. It truly makes a difference!
Landed a Job
Clear explanations, well-structured content, and practical examples that make learning easy and effective. Highly recommended for anyone looking to build or strengthen their skills.
Overview
What you'll learn in
this Live Data Engineering for Data Analyst Bootcamp
Week-1: Advanced SQL Engineering
Phase 01 · Foundations
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Session 1 - SQL for Modern Data Engineering
Advanced joins & query optimization · window functions deep dive · recursive CTEs · MERGE statements · incremental loading patterns · CDC concepts · query execution plans · warehouse optimization
Output: Hands-on: Optimize enterprise-scale SQL workloads · build incremental transformation logic
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Session 2 - Data Modeling & Warehouse Engineering
OLTP vs OLAP · star schema · snowflake schema · fact vs dimension tables · SCD Type 1 & 2 · partitioning strategies · medallion architecture · data contracts
Output: Hands-on: Design retail analytics warehouse · implement SCD Type 2 logic
Week-2: Advanced Python Engineering
Phase 01 · Foundations
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Session 3 - Production Python for Data Engineers
Modular Python architecture · OOP for pipelines · config-driven frameworks · logging · exception handling · retry mechanisms · environment management · secrets handling
Output: Hands-on: Build a reusable ingestion framework
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Session 4 - Advanced Python Data Processing
APIs & ingestion patterns · async processing · parallel execution · file streaming · memory optimization · testing with pytest · packaging basics
Output: Hands-on: Build an API ingestion pipeline
Week-3: PySpark & Distributed Engineering
Phase 02 · Platforms & Cloud
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Session 5 - PySpark Deep Dive
Spark architecture · executors & DAGs · lazy evaluation · partitioning · broadcast joins · shuffle optimization · Spark UI analysis · caching strategies
Output: Hands-on: Optimize large-scale Spark workloads
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Session 6 - Delta Lake & Lakehouse Engineering
Delta internals · ACID transactions · OPTIMIZE & ZORDER · time travel · schema evolution · Change Data Feed · incremental ETL · Bronze / Silver / Gold architecture
Output: Hands-on: Build a medallion architecture pipeline
Week-4: Cloud & Modern Data Platforms
Phase 02 · Platforms & Cloud
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Session 7 - Azure Data Engineering Stack
ADLS Gen2 · Event Hubs · Key Vault · managed identities · Integration Runtime · networking basics · Synapse vs Databricks vs Fabric
Output: Hands-on: Build a secure cloud ingestion architecture
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Session 8 - Microsoft Fabric Engineering
OneLake · Lakehouse · Warehouse · Fabric Data Factory · Eventstream · Real-Time Intelligence · DirectLake · Fabric governance
Output: Hands-on: End-to-end Fabric implementation
Week-5: Analytics Engineering & dbt
Phase 03 · Transformation & Orchestration
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Session 9 - dbt Core Fundamentals
Models · sources · refs() · materializations · snapshots · incremental models · tests · documentation
Output: Hands-on: Build a modular dbt transformation project
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Session 10 - Advanced Analytics Engineering
Macros & Jinja · semantic layer · MetricFlow · SQLFluff · lineage · data quality frameworks · governance · reusable transformation patterns
Output: Hands-on: Enterprise dbt framework implementation
Week-6: Orchestration & Pipeline Engineering
Phase 03 · Transformation & Orchestration
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Session 11 - Apache Airflow Engineering
DAG architecture · dynamic DAGs · sensors · XCom · scheduling · monitoring · retry patterns · failure handling
Output: Hands-on: Build orchestrated ETL workflows
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Session 12 - Enterprise Data Pipelines
Azure Data Factory · Fabric Pipelines · Databricks Workflows · metadata-driven pipelines · config-based orchestration · parameterization · reusable frameworks
Output: Hands-on: Build a metadata-driven orchestration framework
Week-7: Streaming, CI/CD & Reliability
Phase 04 · Production & Launch
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Session 13 - Streaming Data Engineering
Kafka fundamentals · event-driven architecture · Structured Streaming · watermarking · windowing · event-time processing · CDC streaming · Event Hub integration
Output: Hands-on: Real-time streaming pipeline
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Session 14 - CI/CD & Reliability Engineering
Git branching strategies · GitHub Actions · automated testing · deployment pipelines · monitoring · freshness checks · cost optimization · incident management
Output: Hands-on: CI/CD pipeline for data engineering workloads
Week-8: Architecture, Capstone & Career
Phase 04 · Production & Launch
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Session 15 - End-to-End Capstone Project
API ingestion · lakehouse architecture · PySpark transformations · dbt modeling · Airflow orchestration · CI/CD · Power BI reporting · monitoring layer
Output: Hands-on: Enterprise-grade end-to-end implementation
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Session 16 - Interview Preparation & System Design
SQL interview rounds · PySpark interview questions · data modelling rounds · system design · resume transformation · LinkedIn optimization · mock interviews
Output: Hands-on: Mock interview + architecture discussion sessions
The DE Promise
Build & Ship Production Data Pipelines in 10 Weeks.
Not a tutorial. A working end-to-end pipeline defended in front of mentors.
| What you get | Self-study | Other live bootcamps | Our live cohort |
|---|---|---|---|
| Live, mentor-led sessions | |||
| Real projects shipped to GitHub | Rarely | Sometimes | 1 pipeline repo |
| The current 2026 Cloud stack | On your own | Often outdated | |
| Job assistance | |||
| Investment | Your time | ₹2,00,000+ | US$840 |
May we help you?
Frequently Asked
Questions
Q.1
When does the bootcamp officially start?
Q.2
When do I get access after enrolling as an Inner Circle member?
Q.3
What is the Inner Circle, and how is it different from regular enrollment?
Q.4
Do I also get the Data Engineering Bootcamp 1.0?
Q.5
When are the live sessions?
Q.6
What if I miss a live session?
Q.7
What happens after the 8 weeks? Do I lose access?
Q.8
What happens in the Inner Circle curriculum session?
Q.1
Do I need prior data engineering experience?
Q.2
I am a fresher with no work experience. Can I join?
Q.3
Who is this bootcamp designed for?
Q.1
How do I get help if I am stuck?
Q.2
Is there job assistance?
Q.1
What is the Inner Circle price and when does it close?
Q.2
I already own the Data Engineering Bootcamp 1.0. What do I pay?
Q.3
I bought only some individual courses from the Data Engineering Bootcamp 1.0. What do I pay?
Q.1
I used a subsidy and now want to refund this Bootcamp itself. What happens?
Q.2
I used a subsidy (my existing Data Engineering Bootcamp or individual course purchase). Can I refund my original purchase after enrolling?
Q.3
What is the refund policy?
Q.1
When does the bootcamp officially start?
Q.2
When do I get access after enrolling as an Inner Circle member?
Q.3
What is the Inner Circle, and how is it different from regular enrollment?
Q.4
Do I also get the Data Engineering Bootcamp 1.0?
Q.5
When are the live sessions?
Q.6
What if I miss a live session?
Q.7
What happens after the 8 weeks? Do I lose access?
Q.8
What happens in the Inner Circle curriculum session?
Q.1
Do I need prior data engineering experience?
Q.2
I am a fresher with no work experience. Can I join?
Q.3
Who is this bootcamp designed for?
Q.1
How do I get help if I am stuck?
Q.2
Is there job assistance?
Q.1
What is the Inner Circle price and when does it close?
Q.2
I already own the Data Engineering Bootcamp 1.0. What do I pay?
Q.3
I bought only some individual courses from the Data Engineering Bootcamp 1.0. What do I pay?
Q.1
I used a subsidy and now want to refund this Bootcamp itself. What happens?
Q.2
I used a subsidy (my existing Data Engineering Bootcamp or individual course purchase). Can I refund my original purchase after enrolling?
Q.3
What is the refund policy?
Become end-to-end data person in 8 weeks
SQL