Learn Data Engineering for FREE (Snowflake, DBT, SQL & Data Warehouse Tutorials)

Welcome to DataSurface! Your free, hands-on guide to mastering modern data engineering.

The journey to becoming an expert data engineer starts now! This channel is launching a brand-new, FREE series dedicated to teaching you the most in-demand technologies in the data world, with practical, step-by-step tutorials.

We will be doing deep dives into:
- Snowflake
- DBT (Data Build Tool)
- Advanced SQL
- Data Warehousing Concepts
- Cloud Platforms (AWS & Azure)

Whether you're a beginner, changing careers, or upgrading your skills, subscribe and hit the bell icon so you don't miss a single video. Let's build together!

Connect with me:

#DataEngineering #FreeCourse #Snowflake #DBT #SQL #LearnToCode #DataWarehouse #AWS #Azure #Learn Data Engineering for FREE (Snowflake, DBT, SQL & Data Warehouse Tutorials)

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🛠️ Core Technologies Covered
🧮 SQL
🗃️ Data Warehousing
❄️ Snowflake Cloud Platform
🧱 dbt Core
☁️ dbt Cloud
🐍 Python
🔄 Azure DevOps (CI/CD),
🐙 GitHub Code Deployment
✨ Explore other popular tools and technologies in data engineering:
🤖 AI Era: Generative AI and Prompt Engineering Techniques:

📚 Here’s What You’ll Discover in My Playlists:

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📘 Data Fundamentals Series:-
📊 Overview of data & its importance
📈 Growth & evolution of data over time
📚 Legacy systems: OLTP, OLAP, Data Lakes
🧠 Key terminologies in the data space
🏢 Common systems: CRM, MDM, ERP, ODS

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⚙️ Data Engineering Fundamentals Series:-
🔹 What is Data Engineering in 2025 and how the role is evolving
🔹 A complete overview of the Modern Data Stack
🔹 A step-by-step career roadmap to become a data engineer

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🗄️ Database Overview Series:-
💾 What is a Database?
🔄 Evolution of Databases
🧪 Oracle 23c AI Edition – Installation & Features

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🧮 SQL Series:-
📘 Full Oracle SQL syllabus
🔍 Real-world query examples
🎯 SQL Interview prep – tips & tricks

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🏗️ Data Warehouse Series:-
📦 What is a Data Warehouse & Why it's critical?
🔄 ETL vs ELT, SCD's explained
🏛️ Traditional warehouse systems overview

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☁️ Cloud Computing Overview:-
🌐 Cloud Basics – What, Why & How
🆚 AWS vs Azure vs GCP key services

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❄️ Snowflake Cloud Data Platform Series:-
🧱 Snowflake Architecture & Key Concepts
👥 Account Setup & User Management
📥 Data Loading & Unloading
🧠 Advanced Snowflake SQL
⚙️ Virtual Warehouses & Compute Scaling
⏳ Time Travel & Data Recovery
🤝 Data Sharing & Collaboration
🚀 Performance Tuning & Cost Optimization
📓 Snowflake Notebooks & Collaborative Analytics
🧑‍💻 Snowpark for Developers & Data Engineering

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🟠 DBT Core Series – Build, Transform & Trust Your Data:-
📌 Introduction & Project Setup
📊 Models – SQL Transformations
📁 Seeds – Load CSVs
🧪 Tests – Validate Data
📝 Auto Documentation
🔁 Incremental Models
🔧 Jinja Macros
🔗 Data Lineage & Graphs
🔐 Environment Profiles
🤖 GitHub Copilot Productivity

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🟦 DBT Cloud Series – Elevate Your Data Workflows in the Cloud:-
🌐 Introduction to dbt Cloud & Architecture Overview
🧱 Connecting to Your Data Warehouse ( Snowflake, etc.)
📂 Project Setup & GitHub Integration
🧠 Developing Models with the Cloud IDE
📅 Job Scheduling
🔁 Environment Management
📜 Job Logs, Run History & Debugging Tools
🤖 Boosting Development with GitHub Copilot
🌟 Best Practices for Production-Ready dbt Cloud Projects

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🤖 AI in Data Engineering
🧠 Generative AI for Data Workflows
✍️ Prompt Engineering Essentials

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🐍 Python Series :-
🧩 Basics – Variables, Functions, Types
🔁 Loops & Conditionals
📦 Libraries – pandas, numpy, requests
🧹 Data Cleaning with pandas
📄 File Handling – CSV, JSON, Excel

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🔄 Azure DevOps Series:-
📂 Azure Repos, Pipelines & Artifacts
🔀 Branching & Pull Requests
🌱 Git – Clone, Commit, Push
📊 Boards & Wikis

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🐙 GitHub Series :-
🌱 Basics – Clone, Commit, Push, Pull
🔀 Branching Strategies & Pull Requests

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🚀 Start your journey toward becoming a job-ready data engineer — right here.

Stay Updated with My Content:

#LearnSnowflake, #DBTCloud, #FreeSQLTraining, #ModernDataStack, #DataEngineering2025, #DataWarehouse, #DataFundamentals, #DataCareer, #SnowflakeTutorial, #DBTCore, #SQLforBeginners, #CareerInData, #DataEngineering