Snowflake Masterclass: Pipelines, SQL, Streams, Tasks, DBT

Snowflake Masterclass: Pipelines, SQL, Streams, Tasks, DBT | Udemy [Update 02/2026]
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Genre: eLearning

Learn Snowflake from scratch with real-world projects, pipelines, SQL, streams, tasks, dbt, Airflow & dashboards

What you’ll learn:
Understand Snowflake architecture, storage, compute, caching, and micro-partitions
Create and manage warehouses, databases, schemas, tables, and views
Implement Role-Based Access Control (RBAC) with users, roles, and grants
Load data using stages, file formats, COPY INTO, and Snowpipe
Build near real-time pipelines using streams and tasks
Use zero-copy cloning, time travel, and fail-safe for data recovery
Design Snowflake-native pipelines using best practices
Build an end-to-end hotel booking data engineering project inside Snowflake
Build a real-time banking data pipeline using Snowflake, dbt, Airflow, and Kafka
Become job-ready for Snowflake Data Engineer, Analyst, or Cloud roles

From Beginner to Advanced with Real-World Data Engineering Projects

This is a complete, end-to-end Snowflake course designed to take you from absolute beginner to job-ready data engineer using modern, production-level workflows.

Unlike short tutorials, this course focuses on how Snowflake is actually used in real companies, with clear explanations, hands-on demos, and full-scale projects. Every concept is taught practically using Snowflake’s native features and modern data stack tools.

By the end of this course, you will confidently design, build, and manage real data pipelines, understand Snowflake architecture deeply, and showcase portfolio-ready projects.

What You Will Learn (Step-by-Step)

Snowflake Fundamentals & Architecture

What Snowflake is and why companies use it

Snowflake architecture: storage, compute, caching, micro-partitions

Snowflake on AWS, Azure, and GCP

Pricing model and cost optimization basics

Navigating Snowsight UI

Using built-in AI features inside Snowflake

Core Snowflake Concepts

Virtual warehouses and performance tuning

Role-Based Access Control (RBAC): users, roles, grants

Databases, schemas, tables, and table types

Views and materialized views

Zero-copy cloning, Time Travel, and Fail-safe

Data Loading & Pipelines

File formats and internal, external, and named stages

COPY INTO and bulk data loading

Snowpipe and continuous ingestion

Streams and tasks for incremental pipelines

Building near real-time pipelines inside Snowflake

Project 1: Snowflake-Native Hotel Booking Project

End-to-end data engineering project built 100% inside Snowflake

Bronze, Silver, and Gold layers using Medallion Architecture

Data cleaning and validation using SQL

Handling missing, invalid, and corrupted data

Building interactive dashboards using Snowsight

Production-style transformations using pure Snowflake SQL

Project 2: Real-Time Banking Data Engineering Project

Designing OLTP systems with PostgreSQL

Real-time Change Data Capture using Kafka and Debezium

Ingesting streaming data into Snowflake

Transformations using dbt with star schema and SCD Type 2

Workflow orchestration with Apache Airflow

CI/CD automation using GitHub Actions

Connecting Snowflake to Power BI for enterprise dashboards

Tools & Technologies Covered

Snowflake & Snowflake SQL

Snowsight Dashboards

Snowpipe, Streams, Tasks

PostgreSQL

Kafka & Debezium

Apache Airflow

GitHub Actions (CI/CD)

Power BI

Who This Course Is For

Beginners who want to learn Snowflake from scratch

Data Analysts moving into Data Engineering

Data Engineers preparing for Snowflake interviews

Cloud Engineers working with modern data platforms

Anyone building a strong data engineering portfolio

Why This Course Is Different

Beginner to advanced learning path

Real production-style projects

No theory overload — only practical workflows

Snowflake-native and modern data stack approach

Portfolio-ready projects for interviews

Who this course is for:
Beginners who want to learn Snowflake from zero
Aspiring Data Engineers building job-ready skills
Data Analysts transitioning into Data Engineering
Professionals preparing for Snowflake interviews
Cloud Engineers working with modern data platforms
Students looking for real-world, portfolio-ready projects
SQL developers wanting to work with Snowflake
Engineers interested in modern data stacks (dbt, Airflow, Kafka)
Anyone aiming for Snowflake Data Engineer or Architect roles
Learners who prefer practical, production-style workflows

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