Gilberto Hernandez

The release of Apache Iceberg™ v3 tables is a major step for open data architectures. But beyond a version number, what does v3 mean when managing an open lakehouse in Snowflake? This session introduces the Iceberg table format, its evolution and the key breakthroughs of v3. We’ll highlight practical benefits — better CDC support, more efficient handling of semi-structured data and improved metadata management — and show how these features help solve real-world lakehouse challenges. Through a series of live demos, you’ll learn how to get started with v3 features in Snowflake so you can hit the ground running with this new format version.

Modern data engineering is no longer just about moving data or building static data pipelines; it’s about making data AI ready at scale. In this hands-on workshop, we'll build an end-to-end data pipeline to power an AI agent in Snowflake. We'll use Snowflake Openflow to ingest REST API data and semi-structured documents into Snowflake. We'll define our pipeline objects declaratively, implement Dynamic Tables to quickly transform raw data into structured assets, and use Snowflake CoCo along to way to generate new data models and objects. Finally, we'll build a Cortex Agents and use it with Snowflake CoWork to extract insights from the data via a conversational interface.

Stop pipeline sprawl and the cost of data duplication. In this advanced lab, you will learn to perform secure, in-place transformations across your entire data estate. You will connect externally managed Iceberg tables with Catalog Linked Databases to always work on fresh data without ETL, build efficient and declarative pipelines with Dynamic Tables for Iceberg preserving multi-engine access to your data, and implement business continuity to ensure your production data is always available.

To power AI, your data needs a nerve system. For data engineers, the challenge is going beyond the cost of moving data to focus on the instant value of AI activation. This session explores how Snowflake’s connectivity offerings act as the connective tissue for your entire data estate, transforming pipelines from a bottleneck into a strategic enabler. We’ll dive into our AI-driven approach to automation and the latest engineering breakthroughs including the new Datastream service, Snowpipe Streaming, zero-copy integration, Openflow, and file processing, all with Snowflake CoCo. Learn how to build the connective tissue required to light up AI across the enterprise.

In this hands-on tutorial, you'll go from a blank notebook to a fully orchestrated data pipeline built entirely in Python, all in under 90 minutes. You'll learn how to design and deploy end-to-end data pipelines using familiar notebook environments, using Python for your data loading, data transformations, and insights delivery.

In this session, I'll build a complete end-to-end data pipeline from scratch in under 60 minutes, all within Snowflake. I'll demonstrate practical patterns for modern data engineering, from multi-source data integration to end-user delivery.

In this session, I'll build a complete end-to-end data pipeline from scratch in under 60 minutes, all within Snowflake. I'll demonstrate practical patterns for modern data engineering, from multi-source data integration to end-user delivery.

In this hands-on workshop, we’ll explore the combined power of Snowflake’s Data Cloud and dbt. We’ll take raw data housed in Snowflake and transform it using some of dbt's most powerful features to produce a consumable model ready for visualization.