Matthew Farmer

Your raw data is in Snowflake. Your stakeholders want answers from Snowflake CoWork. Between those facts sits the delivery problem: a dimensional model and semantic layer to configure. This session shows both delivered, via JIRA tickets.The first carries the model spec. Maia maps it to your raw schema and conventions, then generates and deploys the ELT pipelines in Snowflake. The second specifies how the model surfaces in Snowflake CoWork. Maia deploys the semantic layer Cortex Analyst uses for natural-language queries.The result is two tickets that are fully queryable, no hand-coded logic or sprint negotiation required.

Data engineering backlogs are the #1 constraint on AI progress. Teams burn out while demand outpaces hiring. This session explores how agentic AI like Maia introduces a new model for scaling data teams—autonomous agents that plan, build, and maintain pipelines end-to-end, shifting teams from reactive ticket fulfillment to proactive AI enablement.

Explore how the rise of agentic ETL and copilots is revolutionizing data engineering. This session will delve into the transformative potential of automation in data integration, reshaping daily workflows, and empowering data teams to focus on innovation rather than routine tasks. Discover how these advancements dramatically enhance productivity, streamline pipeline development, and ensure seamless maintenance in the evolving data landscape. Hear the candid and entertaining views of Joe Reis, best-selling author of "The Fundamentals of Data Engineering."