#Snowflake Data Engineer

A Snowflake Data Engineer specializes in building and managing scalable data pipelines using the Snowflake Data Cloud platform. They handle data ingestion, transformation, and optimization for analytics and reporting. Engineers use SQL, Snowpipe, Streams, and Tasks to automate and manage workflows. This role is in high demand for cloud-based data engineering and modern data warehouse solutions.

✅ Snowflake Cloud DWH
✅ Virtual Warehouses & Compute
✅ Database Objects, Schemas & Cloning
✅ Snowflake SQL, Query Optimization
✅ Time Travel & Zero-Copy Cloning
✅ Snowpipes & Incremental Loads
✅ SnowPark For ETL, ELT
✅ DBT : Data Build Tool
✅ End-to-End Real-Time Project
✅ 1:1 Mentorship, Interview Guidance

Module 1: SQL Concepts & Queries

Ch 1: Data Engineer Job Roles

Introduction to Data
Data Engineer Job Roles
Data Engineer Challenges
Data and Databases Intro

Ch 2: Database Intro & Installations

Database Types (OLTP, DWH, ..)
DBMS: Basics
SQL Server 2025 Installations
SSMS Tool Installation
Server Connections, Authentications

Ch 3: SQL Basics V1 (Commands)

Creating Databases (GUI)
Creating Tables, Columns (GUI)
SQL Basics (DDL, DML, etc..)
Creating Databases, Tables
Data Inserts (GUI, SQL)
Basic SELECT Queries

Ch 4: SQL Basics V2 (Commands, Operators)

DDL: Create, Alter, Drop, Add, modify, etc..
DML: Insert, Update, Delete, select into, etc..
DQL: Fetch, Insert… Select, etc..
SQL Operations: LIKE, BETWEEN, IN, etc..
Special Operators

Ch 5: Data Types

Integer Data Types
Character, MAX Data Types
Decimal & Money Data Types
Boolean & Binary Data Types
Date and Time Data Types
SQL_Variant Type, Variables

Ch 6: Excel Data Imports

Data Imports with Excel
SQL Native Client
Order By: Asc, Desc
Order By with WHERE
TOP & OFFSET
UNION, UNION ALL

Ch 7: Schemas & Batches

Schemas: Creation, Usage
Schemas & Table Grouping
Real-world Banking Database
2 Part, 3 Part & 4 Part Naming
Batch Concept & “Go” Command

Ch 8: Constraints, Keys & RDBMS – Level 1

Null, Not Null Constraints
Unique Key Constraint
Primary Key Constraint
Foreign Key & References
Default Constraint & Usage
DB Diagrams & ER Models

Ch 9: Normal Forms & RDBMS – Level 2

Normal Forms: 1 NF, 2 NF
3 NF, BCNF and 4 NF
Adding Keys to Tables
Cascading Keys
Self Referencing Keys
Database Diagrams

Ch 10: Joins & Queries

Joins: Table Comparisons
Inner Joins & Matching Data
Outer Joins: LEFT, RIGHT
Full Outer Joins & Aliases
Cross Join & Table Combination
Joining more than 2 tables

Ch 11: Views & RLS

Views: Realtime Usage
Storing SELECT in Views
DML, SELECT with Views
RLS: Row Level Security
WITH CHECK OPTION
Important System Views

Ch 12: Stored Procedures

Stored Procedures: Realtime Use
Parameters Concept with SPs
Procedures with SELECT
System Stored Procedures
Metadata Access with SPs
SP Recompilations

Ch 13: User Defined Functions

Using Functions in MSSQL
Scalar Functions in Real-world
Inline & Multiline Functions
Parameterized Queries
Date & Time Functions
String Functions & Queries
Aggregated Functions & Usage

Ch 14: Triggers & Automations

Need for Triggers in Real-world
DDL & DML Triggers
For / After Triggers
Instead Of Triggers
Memory Tables with Triggers
Disabling DMLs & Triggers

Ch 15: Transactions & ACID

Transaction Concepts in OLTP
Auto Commit Transaction
Explicit Transactions
COMMIT, ROLLBACK
Checkpoint & Logging
Lock Hints & Query Blocking
READPAST, LOCKHINT

Ch 16: CTEs & Tuning

Common Table Expression
Creating and Using CTEs
CTEs, In-Memory Processing
Using CTEs for DML Operations
Using CTEs for Tuning
CTEs: Duplicate Row Deletion

Ch 17: Indexes Basics, Tuning

Indexes & Tuning
Clustered Index, Primary Key
Non Clustered Index & Unique
Creating Indexes Manually
Composite Keys, Query Optimizer
Composite Indexes & Usage

Ch 18: Group By Queries

Group By, Distinct Keywords
GROUP BY, HAVING
Cube( ) and Rollup( )
Sub Totals & Grand Totals
Grouping( ) & Usage
Group By with UNION
Group By with UNION ALL

Ch 19: Joins with Group By

Joins with Group By
3 Table, 4 Table Joins
Join Queries with Aliases
Join Queries & WHERE, Group By
Joins with Sub Queries
Query Execution Order

Ch 20: Sub Queries

Sub Queries Concept
Sub Queries & Aggregations
Joins with Sub Queries
Sub Queries with Aliases
Sub Queries, Joins, Where
Correlated Queries

Ch 21: Cursors & Fetch

Cursors: Realtime Usage
Local & Global Cursors
Scroll & Forward Only Cursors
Static & Dynamic Cursors
Fetch, Absolute Cursors

Ch 22: Window Functions, CASE

IIF Function and Usage
CASE Statement Usage
Window Functions (Rank)
Row_Number( )
Rank( ), DenseRank( )
Partition By & Order By

Ch 23: Merge(Upsert) & CASE, IIF

Merge Statement
Upsert Operations with Merge
Matched and Not Matched
IIF & CASE Statements
Merge Statement inside SPs
Merge with OLTP & DWH

Ch 24: Key Take-Aways from Module 1

Case Study 1: Medicare Scenario
Case Study 2: Ecommerce Scenario

Module 2: Snowflake (Cloud ETL, DWH)

Ch 1: Introduction to Snowflake

Database, DWH Introduction
Cloud Data Warehouse
Cloud DWH Implementations
Snowflake Cloud Intro
Snowflake: SaaS Platform

Ch 2: Snowflake Concepts

Snowflake Account (Cloud)
Snowflake Components
Snowflake Editions, Credits
Snowflake Editions
Virtual Private Edition (VPS)
Snowflake Pricing

Ch 3: Architecture, Warehouse

Compute Architecture
Shared Disk Architecture
CPU & Memory in Clusters
Database Query & Data Cycle
ColumnStore, Virtual Warehouse
Classic UI with Snowflake
Massively Parallel Processing

Ch 4: Snowflake DB & Tables

DB Objects and Hierarchy
DB Creation with Snowflake
Snowflake Tables and Usage
Retention Time, Connections
Permanent, Transient Types
CREATE TABLE AS SELECT

Ch 5: Time Travel, Recovery

Time Travel in Snowflake
Invoking Time Travel Feature
Timestamp, Offset, Query ID
Data Recovery, TIMESTAMP
Fail Safe and UNDROP, OFFSET
Transient Tables, Real-time

Ch 6: Schemas and Session Context

Schema Creation Usage
Permanent, Transient Schemas
Managed Schemas in Snowflake
Invoking Schemas & Cloning
Session Context & Schema
Data Loading with GUI

Ch 7: Constraints & Data Types

Constraints & Validations
NULL, NOT NULL Properties
Keys & Constraints, Usage
Inline, Out Of LineConstraints
ENFORCED Constraints
Snowflake Data Types

Ch 8: Snowflake Cloning

Cloning with Snowflake
Zero Copy, Schema Cloning
Snapshot, Metadata
Accessing, Clone
Storage & Metadata Layer
Real-time Considerations

Ch 9: Snowflake Procedures

Procedures and Functions
SQL and JavaScript & CALL
Transactions & Injection
sqlText:command
Cursoring Data and Operations
Dynamic DML with SPs
RETURN, RETURNS Statements

Ch 10: Security Management

Security with Snowflake
Users & Roles in Snowflake
Privileges and Groups
Organization, Account, Users
Creating, Using Roles, Users
System Defined Roles Usage
Role Hierarchy, Dependency
RBAC & DAC in Real-time

Ch 11: Snowflake Transactions

Transaction ACID Properties
Implicit, Explicit and Auto
Durability and Data Storage
current transaction() Usage
to_timestamp_ltz and Usage
Failed Transactions with SPs
Transactions and SPs
Scoped & INNER Transactions

Ch 12: Snowflake Streams & Audits

Snowflake Streams & Usage
Streams and DML Auditing
Snapshot Creation, Offset
METADATA Options & Streams
Auditing DML Operations
Data Flow & Snowflake Streams
Streams on Transient Tables
Time Travel with Stream Tables

Ch 13: Snowflake Tasks, Partitions

Tasks, Serverless Compute
Tasks Tree: Root and DAG
Tasks Schedules and RESUME
User & Snowflake Managed
CRON Syntax with Tasks
Virtual Warehouse Concepts
Multi Cluster Warehouse
Auto Scale Options, Billing

Ch 14: SnowSQL and Variables

SnowSQL Configurations
DDL, DML & SELECT
SnowSQL Command Line
Variables and Batch Process
DECLARE, LET, BEGIN & END
EXECUTE IMMEDIATE, FOR
Creating Virtual Warehouse
Writing Output to Files

Ch 15: Snowflake Partitions, Stages

Snowflake Partitions, Use
Micro Partition with DML, CDC
Cluster Key, Depth and Overlap
Internal Partition Types & Usage
List, Range and Hash Partitions
Snowflake Stages, Types
Internal and External Stages
COPY Command, Bulk Loads

Ch 16: Azure & External Stages

Azure Storage Account, BLOB
SAS: Shared Access Signature
Using SAS Key and FILE PATH
Azure Storage with BLOB
COPY INTO Command Usage
Snowflake Patterns & RegEx
File Formats: Creation, Usage

Ch 17: Snow Pipes & Incr Loads

SnowPipe Incremental Loads
Azure Queues & Integrations
Azure Active Directory
External Stage, Enterprise AD
Snow Pipes and Data Loads
Incremental Data Loads
File Format with Reg Expr

Ch 18: Power BI with Snowflake

Power BI: Big Data Analytics
Snowflake Data Access
Datawarehouse Access
SnowPro Exam Guidance
Certification Guidance

Module 3: Data Build Tool (DBT)

Ch 1: DBT Fundamentals

What is Data Build Tool?
DBT as a data transformation tool
Importance of DBT in ELT workflows
DBT Cloud for data transformations

Ch 2: DBT Models and Materializations

Building models in DBT
Types of materializations
Table, view, incremental materializations
Model configurations

Ch 3: DBT Jinja Templating

Introduction to Jinja
Using Jinja with DBT
Macros and reusable code
Implementing dynamic SQL

Ch 4: DBT Testing and Documentation

Writing and executing tests
Data quality checks
DBT documentation and lineage graphs
Generating DBT docs

Ch 5: DBT Seeds and Sources

Using seeds for static data
Defining and using sources
Source freshness checks
Integrating external data

Ch 6: DBT Deployment and CI/CD

Deployment strategies for DBT
Continuous integration and deployment
Automating DBT workflows
Version control with Git

Ch 7: DBT Best Practices

Project structure recommendations
Coding standards and guidelines
DBT project optimization
Performance tuning tips

Ch 8: Hooks in DBT

Custom scripts to run at specific points
Adding additional logic to streamline Snowflake
Analyses and exploratory data workflows
Ad-hoc analyses that do not get materialized

Ch 9: DBT Snapshots

Managing historical data
Implementing DBT snapshots
Snapshot configuration
Strategies for handling changes

Ch 10: DBT Packages and Extensions

Leveraging DBT packages
Using community packages
Extending DBT functionality
Integrations with other data tools

Ch 11: DBT Advanced Topics

Advanced Jinja usage, Snowpark
Handling complex data scenarios
Custom materializations, Snowpark
Troubleshooting and debugging techniques

Ch 12: Real-time Project Phase 1

Defining project requirements
Initial project setup and DBT configuration
Model planning and development
Initial testing and validation

Ch 13: Real-time Project Phase 2

Project deployment and monitoring
Implementing advanced DBT features
Comprehensive testing and documentation
Real-world deployment considerations

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What is the Snowflake Engineer course and who should join?

This course is meant for Data Engineers, ETL Developers, SQL Developers, BI Engineers, Cloud Engineers, and anyone wanting to build scalable Cloud Data Warehouses using Snowflake. The training combines SQL, Snowflake, and DBT for full-stack ELT development.