Snowflake has quickly become one of the most popular cloud data platforms — and for good reason. Its separation of storage and compute, pay-as-you-go scalability, and unique features like zero-copy cloning and time travel make it a powerful tool for modern data teams.
But for many engineers, the challenge isn’t just what Snowflake can do — it’s how to use it effectively, avoid cost traps, and design for performance from day one.
That’s where this new series comes in.
❄️ What to Expect
Over the coming weeks, I’ll be publishing a guided series on Snowflake that starts with the basics and gradually builds toward advanced engineering practices. Think of it as a roadmap — whether you’re just getting started or looking to fine-tune an existing implementation, you’ll find something useful here.
The series covers:
- Foundations & architecture (what makes Snowflake different, warehouses, stages)
- Working with data (Snowpipe, semi-structured data, modeling)
- Performance tuning (micro-partitions, clustering, caching strategies)
- Governance & reliability (RBAC, time travel, cost control)
- Advanced features (zero-copy cloning, streams & tasks, Snowpark)
- Real-world applications (CI/CD, end-to-end project builds, hybrid platforms)
🚀 Start the Journey
I’ve set up a landing page where you can follow along and see the outline of upcoming posts:
👉 Snowflake Series: From Foundations to Advanced Engineering
Bookmark it — I’ll keep the page updated as each article goes live.
Whether you’re migrating to Snowflake, optimizing queries, or exploring new features like Snowpark, this series is designed to give you practical insights you can put to work immediately.
Stay tuned — the first post drops soon!