Snowflake Summit 2026
Deliver 100× data engineering output
with the same team
See it first hand at Snowflake Summit.
Book your 1:1 at Summit
$100-250k
saved on average per customer from cutting legacy tools
Snowflake
Summit
Summit
When
June 1-4, 2026
Where
Booth #2603
Book
1:1 Meetings available
“Maia offers a glimpse into the future of data engineering.”
“It’s intuitive, powerful, and feels like a real accelerant for how teams build with data. I’m excited about what this will unlock.”
Sridhar Ramaswamy
CEO at Snowflake
Beyond the booth
See what is on our lineup at SPIN, just steps from the Moscone Center | 690 Folsom St #100, San Francisco, CA
The Hive Fest
June 2 | 7pm
Close out Day 2 of Snowflake Summit at The Hive Fest at SPIN, just steps from Moscone.
Reserve your spot
Maia Hands-on Lab
June 1-4 | 12-1:30pm
Register for a hands-on session with Maia and see how to 100x your team’s output.
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Partners and Pancakes
June 3 | 7-8:45am
Register for Partners & Pancakes with Maia at Snowflake Summit. Exclusive to Matillion partners.
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After the Keynote Social
June 1 | 6:30-8:30pm
After the keynote, join Maia at SPIN for drinks, light bites, and good company. Save your spot.
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At booth
Visit our booth for live demos and hands-on sessions with Maia by Matillion, the AI Data Automation platform. See how teams are removing the data bottleneck and freeing up 12,000+ hours.
What's Going On
Can you beat Maia?
On demand
Take the Maia challenge. Bring us your ugliest pipeline and watch Maia handle it.
Maia Demos
Book your spot
Take a 1:1 demo and see how Maia understand, builds, and operates your data infrastructure end-to-end.
Theatre sessions
Every 20 mins
Watch a live a Maia demo and see how to 100x your team’s output.
Catch us on stage
Autonomous data pipelines for explainable AI: from insight to source
ABOUT THE SESSION
When AI insights drive real decisions, one question becomes unavoidable: can you prove where the data came from?
AI analytics tools like Snowflake Intelligence operate on the right side of the stack, generating insights from warehouse data. But trust begins upstream, where data moves through ingestion and transformation pipelines. As AI scales, schema drift, changing sources, and evolving logic make it hard to explain how metrics are produced. Maia closes this gap by autonomously operating the data system that feeds Snowflake—building, executing, and adapting pipelines while capturing context and lineage by default, enabling a clear path from insight to source.
AI analytics tools like Snowflake Intelligence operate on the right side of the stack, generating insights from warehouse data. But trust begins upstream, where data moves through ingestion and transformation pipelines. As AI scales, schema drift, changing sources, and evolving logic make it hard to explain how metrics are produced. Maia closes this gap by autonomously operating the data system that feeds Snowflake—building, executing, and adapting pipelines while capturing context and lineage by default, enabling a clear path from insight to source.
Jun 3 | 1:30 pm ET
Mia McMillan
Senior Product Manager
Matillion
Cyril Sonnefraud
Principal Product Manager
Matillion
Agent-to-agent data supply chains: delivering data at machine scale
ABOUT THE SESSION
Snowflake Intelligence can deliver answers in seconds. The constraint is now data availability latency, getting the right data when it is needed. Most platforms are built to analyze existing data, not respond when new data is required. When data is not in the warehouse, teams must integrate sources, build pipelines, and adapt transformations, delays AI cannot bypass.
This session explores agent to agent coordination. Snowflake Intelligence identifies gaps, while Maia operates upstream to discover sources, generate pipelines, reconcile schemas, and deliver queryable datasets in minutes without manual intervention.
This session explores agent to agent coordination. Snowflake Intelligence identifies gaps, while Maia operates upstream to discover sources, generate pipelines, reconcile schemas, and deliver queryable datasets in minutes without manual intervention.
June 4 | 4:00pm
Matt Farmer
Director of Product
Matillion
Arawan Gajajiva
Principal Architect - Sales Engineering COE
Matillion
Stop asking, start knowing: turning tribal knowledge into continuous insight
ABOUT THE SESSION
Enterprise data platforms assume humans ask questions and platforms return answers. But the most valuable knowledge rarely lives in tables. It lives in Slack threads, analyst notes, business reviews, and institutional memory.
This session introduces a model where AI does not wait to be asked. We show how platforms capture tribal knowledge as a byproduct of everyday workflows, feeding a living context engine. With Maia, teams see up to 90% reduction in manual data engineering work and, in some cases, up to 100x improvement in throughput. AI agents use this context to run analysis and surface reporting autonomously, with feedback loops that improve the system over time.When AI insights drive real decisions, one question becomes unavoidable: can you prove where the data came from?
This session introduces a model where AI does not wait to be asked. We show how platforms capture tribal knowledge as a byproduct of everyday workflows, feeding a living context engine. With Maia, teams see up to 90% reduction in manual data engineering work and, in some cases, up to 100x improvement in throughput. AI agents use this context to run analysis and surface reporting autonomously, with feedback loops that improve the system over time.When AI insights drive real decisions, one question becomes unavoidable: can you prove where the data came from?
June 1 | 1:30pm
Julian Wiffen
Chief of AI and Data Science
Matillion
Liam Morrison
Vice President, Field Engineering
Matillion
80x faster data engineering: from prompts to pipelines with Maia
ABOUT THE SESSION
What happens when complex data engineering work can be delegated to AI agents? In this session, Jason Mulvin, Director of Enterprise Data & Analytics at Sophos, shares how his team designs pipelines through prompting - accelerating development, testing, and deployment. Sophos uses agents to generate pipelines, convert legacy workflows, and analyze existing ones.
In one example, a pipeline that would take five days was generated and validated in under 30 minutes, achieving 95–99% completion and producing automated tests. Sophos is now reviewing 1,400+ pipelines to identify optimizations and inconsistencies. This session shows how prompts translate into production pipelines.
In one example, a pipeline that would take five days was generated and validated in under 30 minutes, achieving 95–99% completion and producing automated tests. Sophos is now reviewing 1,400+ pipelines to identify optimizations and inconsistencies. This session shows how prompts translate into production pipelines.
June 2 | 3:30pm
Jason Mulvin
Director, Enterprise Data and Analytics
Sophos
Joe Herbert
Principal Solution Architect (Maia)
Matillion
Who you will meet
Some of our best people will be at Snowflake Summit. Here's who you'll find on the floor and at SPIN.
Matthew Scullion
CEO
Ed Thompson
CTO
Frank Weigel
CPO
Tim O'Neil
CRO
Mark Johnston
CMO
Joe Herbert
Principal Solution Architect
Angie Hastings
Sr. Solution Architect
Zach Ennis
Sr Solution Architect
Mike Harms
Manager, Field Engineering
Cryril Sonnefraud
Principal Product Manager
Mike Terrell
Sales Engineer
Julian Wiffen
Chief of AI & Data Science
Your Snowflake investment is only as good as the pipelines feeding it
Most data teams are stuck in a cycle: requests pile up, engineers burn down the backlog manually, deployments slip. Every new AI initiative joins the queue. And the queue never gets shorter.
The setup tax
Pipeline configuration still takes days, not hours
Downstream damage
Bottlenecks slow down every analytics and AI project that depends on clean data
Always behind
Deployment cycles lag behind business demand
No time left
Governance and documentation fall behind because there's simply no time
Your Snowflake pipelines shouldn’t need a team of engineers to keep them running
Maia designs, builds, and operates them autonomously, so your data team can focus on what actually moves the business. See it live at Summit.
Book a 1:1 at Summit
Your agentic AI data team — native to Snowflake
Where copilots suggest, Maia acts. It reasons, plans, and executes complex data engineering tasks end-to-end — designing, building, testing, documenting, and operating production-grade pipelines at machine speed, with governance built in.
Built into the Data Productivity Cloud, Maia works natively with Snowflake — adapting dynamically to schema or source changes, applying enterprise controls automatically, and integrating seamlessly with Snowflake features including Snowpark, Cortex, and AI Data Services.
Built into the Data Productivity Cloud, Maia works natively with Snowflake — adapting dynamically to schema or source changes, applying enterprise controls automatically, and integrating seamlessly with Snowflake features including Snowpark, Cortex, and AI Data Services.
From Request to Live in Four Steps
Request
One prompt, capture your business requirements.
Maia plans
Reviews your data. Proposes the plan.
Maia builds & test
Pipeline built and validated. PR ready.
Live in Snowflake
Production-grade, AI-ready data.
Autonomous execution
Plans, builds, and runs pipelines end-to-end
Enterprise governance
Security, lineage, and compliance applied automatically
Snowflake-native speed
Processes, deploys, and scales inside your Snowflake account
Built for what data teams actually need
Most platforms solve part of the problem. Maia covers all of it — from first request to production-grade pipeline, without the bottlenecks.
Scale without headcount
Maia augments human expertise with autonomous execution — designing, building, testing, and operating production-grade pipelines at machine speed, helping organizations increase delivery capacity without increasing headcount.
One platform, not a patchwork
The Data Productivity Cloud unifies data integration, transformation, orchestration, and monitoring in a single platform. Combined with Snowflake's native scalability, customers replace fragmented tooling with a governed, seamless experience.
From backlog to production — in days
With Snowflake as the foundation and Maia embedded within Matillion, customers move from proof-of-concept to production in days, not months. Engineering teams accelerate pipeline delivery by up to 10×, enabling AI and analytics initiatives to launch on schedule.
Your Snowflake pipelines shouldn’t need a team of engineers to keep them running
Maia designs, builds, and operates them autonomously, so your data team can focus on what actually moves the business. See it live at Summit.
Book a 1:1 at Summit
Data professionals love Maia
Maia automates manual data work for teams at global enterprises and fast-growing startups alike.
“Maia is helping us become an AI-ready organization by transforming how we build pipelines. In some cases we’ve seen pipeline build time go from 2 days to 10 minutes.”
John Tentomas
CEO Nature’s Touch
“Maia replaced thousands of hours of manual work, helped us de-risk audits, and let business teams generate insights in days instead of months. It’s the first AI investment that delivered value fast.”
Group CFO
Global Financial Services Firm
"Maia feels like having a team of junior data engineers who never sleep. We’re a small team, but with Maia we’re punching well above our weight."
Dan Adams
Global Analytics Manager @ Edmund Optics
Built for Snowflake, Backed by Snowflake
Snowflake Marketplace
Deploy in minutes, funded through your existing Snowflake commitment
Snowflake Ventures
Strategic investment, not just partnership
Native integrations
Snowpark, Cortex, AI Data Services, OpenFlow extension