Snowflake Summit 2026
Deliver 100× data engineering output
with the same team
See it first hand at Snowflake 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
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.
Reserve your spot
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.
Reserve your spot
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
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 Maia demo and see how to 100x your team’s output.
Catch us on stage
8:47am request. 9:30am production. Agentic data teams on Snowflake.
ABOUT THE SESSION
8:47am, Monday. Your analyst Slacks: can we get active-customer churn by tier for the board deck at 10? In most data teams, that’s a sprint ticket. For a team running Maia on Snowflake, it’s live by 9:30.
This session walks through a day in the life of a data engineer who moves from request handler to operator. Maia reads Snowflake schemas, dbt models, and team context, so “active customer” means what finance means. It handles urgent requests, clears Jira backlog, converts PowerCenter to Snowflake-native ELT, and hands governed data products to Cortex and Snowflake Intelligence.
Live build. Proven at Cisco, Docusign, and Mercedes F1.
This session walks through a day in the life of a data engineer who moves from request handler to operator. Maia reads Snowflake schemas, dbt models, and team context, so “active customer” means what finance means. It handles urgent requests, clears Jira backlog, converts PowerCenter to Snowflake-native ELT, and hands governed data products to Cortex and Snowflake Intelligence.
Live build. Proven at Cisco, Docusign, and Mercedes F1.
Jun 3 | 1:30 pm ET
Mia McMillan
Senior Product Manager
Matillion
Cyril Sonnefraud
Principal Product Manager
Matillion
From star schema to Snowflake Intelligence in two Jira tickets.
ABOUT THE SESSION
Your raw data is in Snowflake. Your stakeholders want answers from Snowflake Intelligence. 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 Intelligence. Maia deploys the semantic layer Cortex Analyst uses for natural-language queries.Two tickets that are fully queryable. No hand-coded logic or sprint negotiation.
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 Intelligence. Maia deploys the semantic layer Cortex Analyst uses for natural-language queries.Two tickets that are fully queryable. No hand-coded logic or sprint negotiation.
June 3 | 4:00pm
Matt Farmer
Director of Product
Matillion
Arawan Gajajiva
Principal Architect - Sales Engineering COE
Matillion
When context matters: Maia teaches Snowflake Intelligence your business
ABOUT THE SESSION
The anomaly lived for three weeks between the QBR metric definition and pipeline logic. Nobody caught it until the number was in the board pack. The alternative is Maia: a system where context builds as your team works. The Context Engine captures tribal knowledge from Slack, analyst notes, and BRDs, building context around metrics, rules, exceptions, and naming conventions.
Mission Control runs agents that monitor data movements against that context, spot mismatches, and start the investigation.We’ll show Maia catching a data movement, explaining what changed, then handing Snowflake Intelligence a structured path for deeper exploration.
Mission Control runs agents that monitor data movements against that context, spot mismatches, and start the investigation.We’ll show Maia catching a data movement, explaining what changed, then handing Snowflake Intelligence a structured path for deeper exploration.
June 2 | 3:30pm
Julian Wiffen
Chief of AI and Data Science
Matillion
Liam Morrison
Vice President, Field Engineering
Matillion
Agentic data engineering at Sophos: Moving from pilot to production with Maia
ABOUT THE SESSION
95% of AI pilots never reach production. Sophos, a billion-dollar cybersecurity company facing a large Informatica migration and growing pipeline backlog, did it in under a year using Maia.
In this session, Enterprise Data Architect Jason Mulvin shares how his team navigated real enterprise challenges: legal and AI governance, bridging ETL gaps, and adapting dev standards for agentic tooling. The result: pipelines generated in minutes, a multi-year backlog becoming manageable — without adding headcount. What could your team achieve by next Summit?
In this session, Enterprise Data Architect Jason Mulvin shares how his team navigated real enterprise challenges: legal and AI governance, bridging ETL gaps, and adapting dev standards for agentic tooling. The result: pipelines generated in minutes, a multi-year backlog becoming manageable — without adding headcount. What could your team achieve by next Summit?
June 1 | 1:30pm
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