Snowflake & Dbt Mastery Bootcamp The Complete Guide

Snowflake & Dbt Mastery Bootcamp: The Complete Guide
Published 7/2026
Created by manish tiwari
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All Levels | Genre: eLearning | Language: English | Duration: 182 Lectures ( 24h 20m ) | Size: 14.6 GB​

Master Snowflake & dbt Core with SQL, Snowpipe, ELT, AWS Integration, Security & Real-World Projects
What you'll learn
Understand Snowflake architecture and how cloud data warehousing works
Set up a Snowflake account and confidently navigate the Snowsight UI.
Create and manage databases, schemas, tables, and virtual warehouses.
Master SQL in Snowflake, including DDL, DML, joins, and data manipulation commands.
Load data into Snowflake using internal stages, user stages, table stages, and external stages.
Install and use SnowSQL to automate data loading and Snowflake administration.
Configure and implement Snowpipe for continuous, automated data ingestion from Amazon S3.
Integrate Snowflake with AWS services using IAM roles, S3, and external stages.
Work with advanced Snowflake features such as Time Travel, Zero-Copy Cloning, Streams, Views, and Caching.
mplement role-based access control (RBAC), grants, and data masking to secure Snowflake environments.
Gain the practical Snowflake skills required for Data Engineer, Data Analyst, Cloud Data Engineer, and Snowflake Developer roles.
Requirements
Basic understanding of computers and the internet
No prior experience is required - everything will be explained from scratch
A computer with internet connection to access Snowflake , AWS services and practice the labs
Description
Snowflake & dbt Mastery Bootcamp: The Complete Guide
MasterSnowflake anddbt Core from beginner to advanced through hands-on labs, real-world projects, and production-ready ELT pipelines. Learn SQL, Snowpipe, COPY INTO, Incremental Models, Snapshots, Jinja, Macros, AWS Integration, Security, and modern Data Engineering best practices.
Become a confidentData Engineer by mastering Snowflake and dbt through practical, hands-on learning and real-world projects. This comprehensive bootcamp takes you from the fundamentals to advanced concepts, equipping you with the skills needed to design modern cloud data warehouses, build scalable ELT pipelines, and develop production-ready data transformation workflows.
Whether you're a beginner starting your Data Engineering journey or an experienced professional looking to upskill, this course provides a structured learning path with enterprise best practices, practical demonstrations, and real-world use cases.
Unlike courses that focus only on Snowflake or only on dbt, this bootcamp teaches how both technologies work together to build scalable, maintainable, automated, and production-ready cloud data platforms used by modern organizations.
Throughout this course, you'll learn how to design Snowflake environments, write efficient SQL, load and transform data, build modular dbt Core projects, implement testing and documentation, automate workflows, apply modern Data Modeling techniques, secure enterprise data, and integrate Snowflake with AWS.
What You'll Learn
Snowflake
Snowflake Architecture and Cloud Data Warehouse Concepts
Creating and Managing Snowflake Accounts
Snowsight User Interface
Virtual Warehouses, Compute Scaling, and Performance Optimization
Databases, Schemas, Tables, and Views
SQL Fundamentals and Advanced SQL
Joins, Aggregations, Window Functions, and SQL Best Practices
Data Loading using COPY INTO
Incremental Data Loading Strategies
File Formats and Data Loading Patterns
Internal, User, Table, Named, and External Stages
SnowSQL Installation and Practical Usage
AWS S3 Integration with Snowflake
IAM Role Configuration
Snowpipe for Continuous Data Ingestion
Snowpipe Monitoring
Streams and Tasks for Data Automation
Time Travel
Zero-Copy Cloning
Query Performance Optimization
Result Cache and Warehouse Cache
Role-Based Access Control (RBAC)
Dynamic Data Masking
Snowflake Security and Governance Best Practices
dbt Core (Data Build Tool)
Installing and Configuring dbt Core
dbt Project Structure
Models and Materializations
ref() Function
source() Function
Tags and Model Configuration
Variables and Environment Management
Sources and Source Freshness
Seeds
Incremental Models
Snapshots for Historical Data Tracking
Generic Tests
Custom Tests
Documentation Generation
Macros
Jinja Templating
Hooks
dbt Packages
Building Modular and Reusable Data Transformation Pipelines
Analytics Engineering Best Practices
Real-World Hands-on Projects
Throughout the course, you'll work on practical projects that simulate real enterprise Data Engineering scenarios.
You'll build
End-to-End Snowflake Data Warehouse Project
AWS S3 to Snowflake Data Loading Project
Snowpipe Continuous Data Ingestion Project
Incremental ELT Pipeline using dbt Core
SCD Type 1 Data Warehouse Project
Production-Ready Data Transformation Pipeline
Automated Data Validation using dbt Tests
dbt Documentation and Metadata Generation
Why Take This Course?
Comprehensive Snowflake & dbt Bootcamp in a single course
Beginner-friendly with step-by-step explanations
100% Hands-on Practical Demonstrations
Real-World Data Engineering Projects
Production-Ready ELT Development
Modern Data Warehouse Best Practices
Enterprise-Level Use Cases
Practical Exercises and Assignments
Interview-Oriented Explanations
Downloadable Resources
Lifetime Access with Regular Course Updates
Who Should Enroll?
Data Engineers
Analytics Engineers
SQL Developers
ETL Developers
BI Developers
Data Analysts
Cloud Engineers
Azure Data Engineers
AWS Data Engineers
Software Engineers transitioning to Data Engineering
Students preparing for Snowflake, dbt Core, Analytics Engineer, and Data Engineer interviews
Anyone interested in Modern Data Engineering
Who this course is for
Beginners who want to learn Snowflake from scratch with hands-on practical examples.
Data Engineers looking to build or strengthen their Snowflake skills for real-world projects.
Data Analysts who want to query, analyze, and manage data using Snowflake.
ETL Developers migrating from traditional data warehouses to Snowflake.
Cloud Engineers working with AWS, Azure, or Google Cloud data platforms.
Students preparing for Snowflake interviews and technical assessments.
Anyone interested in learning enterprise-level data loading, SnowSQL, Snowpipe, security, and automation in Snowflake.
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