Snowflake Masterclass: Pipelines, Sql, Streams, Tasks, Dbt

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

Requirements
Basic understanding of SQL is helpful but not mandatory
Beginner-friendly explanations are provided from scratch
Willingness to learn data engineering concepts
Free Snowflake trial account (setup shown in the course)
Everything else is taught step-by-step in the course

Description
From Beginner to Advanced with Real-World Data Engineering ProjectsThis 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 & ArchitectureWhat Snowflake is and why companies use itSnowflake architecture: storage, compute, caching, micro-partitionsSnowflake on AWS, Azure, and GCPPricing model and cost optimization basicsNavigating Snowsight UIUsing built-in AI features inside Snowflake Core Snowflake ConceptsVirtual warehouses and performance tuningRole-Based Access Control (RBAC): users, roles, grantsDatabases, schemas, tables, and table typesViews and materialized viewsZero-copy cloning, Time Travel, and Fail-safe Data Loading & PipelinesFile formats and internal, external, and named stagesCOPY INTO and bulk data loadingSnowpipe and continuous ingestionStreams and tasks for incremental pipelinesBuilding near real-time pipelines inside Snowflake Project 1: Snowflake-Native Hotel Booking ProjectEnd-to-end data engineering project built 100% inside SnowflakeBronze, Silver, and Gold layers using Medallion ArchitectureData cleaning and validation using SQLHandling missing, invalid, and corrupted dataBuilding interactive dashboards using SnowsightProduction-style transformations using pure Snowflake SQL Project 2: Real-Time Banking Data Engineering ProjectDesigning OLTP systems with PostgreSQLReal-time Change Data Capture using Kafka and DebeziumIngesting streaming data into SnowflakeTransformations using dbt with star schema and SCD Type 2Workflow orchestration with Apache AirflowCI/CD automation using GitHub ActionsConnecting Snowflake to Power BI for enterprise dashboards Tools & Technologies CoveredSnowflake & Snowflake SQLSnowsight DashboardsSnowpipe, Streams, TasksPostgreSQLKafka & DebeziumdbtApache AirflowGitHub Actions (CI/CD)Power BI Who This Course Is ForBeginners who want to learn Snowflake from scratchData Analysts moving into Data EngineeringData Engineers preparing for Snowflake interviewsCloud Engineers working with modern data platformsAnyone building a strong data engineering portfolio Why This Course Is DifferentBeginner to advanced learning pathReal production-style projectsNo theory overload — only practical workflowsSnowflake-native and modern data stack approachPortfolio-ready projects for interviews

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