Free Download Snowflake Master Class Cloud-Native Data EngineeringPublished 3/2026
Created by Snowbrix Academy
MP4 |
Video: h264, 1920x1080 |
Audio: AAC, 44.1 KHz, 2 Ch
Level: All Levels |
Genre: eLearning |
Language: English |
Duration: 36 Lectures ( 2h 41m ) |
Size: 741 MB
✓ Design Snowflake architecture for 100TB+ warehouses with clustering, materialized views, and Streams for real-time pipelines.
✓ Optimize SQL queries 10x using window functions, query profiles, and warehouse sizing-see real cost breakdowns.
✓ Build production DBT models with Snowflake: testing, incremental loads, cost controls, and deployment via GitHub Actions.
✓ Migrate Oracle/Redshift to Snowflake: assess schemas, rewrite queries, validate data with zero downtime patterns.
✓ Implement Snowflake security: RBAC, column masking, row-level access policies, and audit logging for enterprise compliance
Requirements.
Requirements● Basic SQL knowledge (SELECT, JOIN, GROUP BY). No Snowflake account needed-we use free trials.
● Comfort with command line basics (cd, ls, git clone). All code provided as copy-paste templates.
● Free tools only: Snowflake 30-day trial, VS Code, Python 3.10+. No paid services required.
● Data engineering mindset: you want production patterns, not toy examples. Beginners and seniors both welcomed.
DescriptionMost Snowflake tutorials teach you how to run a SELECT. This course teaches you how Snowflake thinks - and that changes everything.
You will leave knowing why Snowflake's 3-layer architecture outperforms every traditional warehouse, how to size and cost-control
virtual warehouses before you build, and how to load millions of rows without writing a scheduler. You will implement Change Data
Capture with Streams and Dynamic Tables, lock down production data with RBAC and column masking, and recover from a midnight DELETE
in under 3 minutes using Time Travel.
Every lesson opens with a real incident. Every pattern is production-grade. Every anti-pattern comes from an actual mistake that
cost someone credits.
What you will learn
- Snowflake architecture: Cloud Services, Virtual Warehouses, micro-partitions, and partition pruning
- Virtual Warehouses: sizing, auto-suspend, multi-cluster scaling, workload isolation, and the credit model
- Data loading: internal and external stages, COPY INTO, Snowpipe continuous ingestion, and VARIANT columns for semi-structured
JSON and Parquet data
- Advanced SQL: CTEs, window functions, the QUALIFY clause, and Query Profile optimization
- Pipelines: Streams for change data capture, Tasks for scheduling, and Dynamic Tables for declarative pipeline management
- Security and governance: RBAC role hierarchy, column masking policies, row access policies, network policies, and ACCESS_HISTORY
for compliance auditing
- Time Travel, zero-copy cloning, and native data sharing with no ETL
- Modern development: Snowpark Python, Cortex AI LLM functions, Streamlit in Snowflake, and Notebooks
- Cost optimization: the five anti-patterns that waste thousands of dollars, and napkin math for estimating costs before you build
What you will build
- A multi-warehouse architecture with workload isolation and auto-suspend
- A Snowpipe continuous ingestion pipeline triggered by cloud events
- A CDC pipeline using Streams + Tasks + MERGE for upsert workloads
- A GDPR-compliant platform using Row Access Policies + Column Masking + Access History
- A cost model to estimate spend before you provision anything
- Streamlit dashboards running inside Snowflake with Cortex AI sentiment scoring
Included: a 45-question practice test - 5 scenario-based questions per module - to verify you can apply what you learned, not just
recall it.
This course is for data engineers moving to Snowflake, analytics engineers who want to understand what runs under their SQL, and
architects designing a new Snowflake deployment.
This is the course that takes you from Snowflake user to Snowflake engineer.
Who this course is for■ Junior data engineers who want Snowflake production patterns that scale to enterprise workloads-starting from first queries.
■ Mid-level DEs stuck on slow queries, high costs, or complex ETL-ready for optimization techniques that deliver 10x performance.
■ Senior architects planning Oracle/Redshift migrations needing zero-downtime strategies and real cost models.
■ Teams building DBT + Snowflake pipelines wanting production-grade testing, deployment, and monitoring patterns.
■ BI developers and Snowflake analysts transitioning into data engineering who want real pipelines and production SQL depth.
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