LIVE Data Engineering Bootcamp for Analysts: Become the End-to-End Data Professional

4.9

(1943 Verified ratings)

Data Analyst → AI-Enabled Data Engineer

Transform from a Data Analyst into an AI-Enabled Data Engineer through Codebasics' live 8-week cohort designed for working professionals. Learn advanced SQL, PySpark, dbt, Airflow, Microsoft Fabric, CI/CD, and production-grade data engineering workflows while building and shipping a complete end-to-end pipeline. Classes run live every Saturday and Sunday, 4 to 7 PM IST — fully interactive, with hands-on labs and real-time Q&A, and recordings available for revision. Limited seats available.

8

Weeks


16

Live Sessions


10+

Tools & Platforms

8

Capstone Layers


1 Year

Access to Class Recordings


98+

Enrolled Learners

LIVE Data Engineering Bootcamp for Analysts: Become the End-to-End Data Professional
US$840
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8

Weeks


16

Live Sessions


10+

Tools & Platforms

8

Capstone Layers


1 Year

Access to Class Recordings


98+

Enrolled Learners

What Makes This Bootcamp Different?

  • 100% LIVE, instructor-led sessions across 8 weeks. Real-time Q&A, live walk-throughs, and direct doubt-clearing with the faculty.

  • 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.

  • 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.

  • Designed and taught by data industry experts & engineering leaders with real-world experience building and shipping production data systems at scale.

  • Master the complete modern DE stack: Python, PySpark, Delta Lake, Databricks, Microsoft Fabric, dbt, Airflow, Kafka, ADF, GitHub Actions, Power BI & more.

  • Production-first mindset: Spark internals, OPTIMIZE & ZORDER, schema evolution, idempotency, CI/CD, observability - the engineering practices that matter in production data systems.

  • Streaming engineering with Kafka, Structured Streaming, watermarking, windowing, and event-time processing - the patterns Indian product teams run today.

  • AI-Assisted Data Engineering: Copilot, Cursor, and Claude Code for SQL, dbt, PySpark, and Airflow - the productivity patterns top DE teams are adopting now.

  • 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.

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Our content is rated 4.9/5 from 18458+ Learners

Overview

What you'll learn in
this Live Data Engineering for Data Analyst Bootcamp

Week-1: Advanced SQL Engineering

Phase 01 · Foundations

  • 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


  • 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

  • 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


  • 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

  • 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


  • 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

  • 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


  • 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

  • Session 9 - dbt Core Fundamentals

    Models · sources · refs() · materializations · snapshots · incremental models · tests · documentation

    Output: Hands-on: Build a modular dbt transformation project


  • 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

  • Session 11 - Apache Airflow Engineering

    DAG architecture · dynamic DAGs · sensors · XCom · scheduling · monitoring · retry patterns · failure handling

    Output: Hands-on: Build orchestrated ETL workflows


  • 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

  • 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


  • 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

  • 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


  • 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?

Saturday, 20 June 2026, a few days after the Inner Circle session.

You are securing your seat now. Full bootcamp access opens on 20 June 2026.

The Inner Circle is early enrollment, open until 16 June 2026. Inner Circle members enroll at a reduced price and get a dedicated live session a few days before the bootcamp launches on 20 June to help shape the curriculum through their feedback. You are not just enrolling early, you are influencing what gets built.

Yes. Every enrollment includes full access to the Data Engineering Bootcamp 1.0 at no extra cost. It includes Job Assistance, Live Problem Solving, and a Virtual Internship. You get both for the price of one.

Saturdays and Sundays, 4 to 7 PM IST. Sessions are fully live and interactive with hands-on labs and real-time Q&A. Recordings are available for revision.

All live sessions are recorded and available within 24 hours. You can catch up at your own pace, though live attendance is strongly recommended as the labs and discussions are where most of the real learning happens.

No. You keep access to all session recordings for 1 year from the bootcamp start date.

All Inner Circle members join a live session with the core team a few days before 20 June 2026. You bring real analyst-to-engineer problems, the stacks your team is moving to, and the gaps you want filled. What you share directly shapes the deep-dives, labs, and capstone tracks. The exact date is communicated to Inner Circle members after enrollment.

Q.1 Do I need prior data engineering experience?

No. This bootcamp is built for working data analysts who want to cross into data engineering. If you have at least 1 year of analyst experience and are comfortable with SQL, you are ready.

We strongly advise against it. This bootcamp moves fast and assumes analyst-level SQL fluency and data literacy. If you are starting from zero, the Codebasics Data Analytics Bootcamp is the right first step. Build that foundation and come back.

Working data analysts, BI developers, and business analysts with 1 to 4 years of experience who want to own the full data stack, not just the dashboard layer. If you already work as a data engineer, this bootcamp is likely below your current level.

Q.1 How do I get help if I am stuck?

Every enrolled learner gets access to the Discord community where you can ask questions, connect with fellow learners, share progress, and learn from each other throughout the bootcamp. The mentor team also provides weekly hands-on lab support.

The Data Engineering Bootcamp 1.0 included with your enrollment has dedicated job assistance. The bootcamp itself focuses on building your skills, shipping a production-grade capstone on GitHub, and preparing you for system design interviews with the core faculty.

Q.1 What is the Inner Circle price and when does it close?

Inner Circle enrollment is open until 16 June 2026. After that, Standard pricing opens from 17 June 2026 until the bootcamp starts on 20 June 2026.

The amount you paid for the Data Engineering Bootcamp 1.0 is fully adjusted and deducted from your enrollment fee.

The amount you paid for those individual courses is deducted from your enrollment fee.

Q.1 I used a subsidy and now want to refund this Bootcamp itself. What happens?

You get back the amount you actually paid for this Bootcamp. Your original purchase stays intact and you keep access to it.

No. Once your existing purchase is applied as a subsidy to reduce your price, that original purchase becomes non-refundable.

Full refund, no questions asked, if you request it on or before 22 June 2026. That is after the first two live sessions (20 and 21 June), so you can see exactly how the bootcamp runs before deciding.

Q.1 When does the bootcamp officially start?

Saturday, 20 June 2026, a few days after the Inner Circle session.

You are securing your seat now. Full bootcamp access opens on 20 June 2026.

The Inner Circle is early enrollment, open until 16 June 2026. Inner Circle members enroll at a reduced price and get a dedicated live session a few days before the bootcamp launches on 20 June to help shape the curriculum through their feedback. You are not just enrolling early, you are influencing what gets built.

Yes. Every enrollment includes full access to the Data Engineering Bootcamp 1.0 at no extra cost. It includes Job Assistance, Live Problem Solving, and a Virtual Internship. You get both for the price of one.

Saturdays and Sundays, 4 to 7 PM IST. Sessions are fully live and interactive with hands-on labs and real-time Q&A. Recordings are available for revision.

All live sessions are recorded and available within 24 hours. You can catch up at your own pace, though live attendance is strongly recommended as the labs and discussions are where most of the real learning happens.

No. You keep access to all session recordings for 1 year from the bootcamp start date.

All Inner Circle members join a live session with the core team a few days before 20 June 2026. You bring real analyst-to-engineer problems, the stacks your team is moving to, and the gaps you want filled. What you share directly shapes the deep-dives, labs, and capstone tracks. The exact date is communicated to Inner Circle members after enrollment.

Q.1 Do I need prior data engineering experience?

No. This bootcamp is built for working data analysts who want to cross into data engineering. If you have at least 1 year of analyst experience and are comfortable with SQL, you are ready.

We strongly advise against it. This bootcamp moves fast and assumes analyst-level SQL fluency and data literacy. If you are starting from zero, the Codebasics Data Analytics Bootcamp is the right first step. Build that foundation and come back.

Working data analysts, BI developers, and business analysts with 1 to 4 years of experience who want to own the full data stack, not just the dashboard layer. If you already work as a data engineer, this bootcamp is likely below your current level.

Q.1 How do I get help if I am stuck?

Every enrolled learner gets access to the Discord community where you can ask questions, connect with fellow learners, share progress, and learn from each other throughout the bootcamp. The mentor team also provides weekly hands-on lab support.

The Data Engineering Bootcamp 1.0 included with your enrollment has dedicated job assistance. The bootcamp itself focuses on building your skills, shipping a production-grade capstone on GitHub, and preparing you for system design interviews with the core faculty.

Q.1 What is the Inner Circle price and when does it close?

Inner Circle enrollment is open until 16 June 2026. After that, Standard pricing opens from 17 June 2026 until the bootcamp starts on 20 June 2026.

The amount you paid for the Data Engineering Bootcamp 1.0 is fully adjusted and deducted from your enrollment fee.

The amount you paid for those individual courses is deducted from your enrollment fee.

Q.1 I used a subsidy and now want to refund this Bootcamp itself. What happens?

You get back the amount you actually paid for this Bootcamp. Your original purchase stays intact and you keep access to it.

No. Once your existing purchase is applied as a subsidy to reduce your price, that original purchase becomes non-refundable.

Full refund, no questions asked, if you request it on or before 22 June 2026. That is after the first two live sessions (20 and 21 June), so you can see exactly how the bootcamp runs before deciding.

Become end-to-end data person in 8 weeks

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