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About this event
Snowflake Summit Attendee List
Event type: Data cloud, analytics, AI/ML, data engineering, platform engineering, security, modern data stack, enterprise technology
Audience profile: Highly commercial, enterprise-focused, and tech-forward. This is one of the strongest events for targeting data buyers, cloud decision-makers, analytics leaders, engineering teams, and vendor evaluation stakeholders.
Overview
Snowflake Summit is a premium technology event built around data infrastructure, analytics modernization, AI adoption, cloud governance, and enterprise transformation. It attracts a mix of technical and business audiences, but the strongest buying signals come from companies actively investing in data platforms, cloud migration, governance, machine learning, business intelligence, data sharing, and scalable analytics.
For attendee-list selling, this event is especially valuable because the audience includes budget holders, technical implementers, and strategic evaluators. The best leads are usually not just general attendees, but the leaders responsible for data strategy, cloud architecture, analytics transformation, and vendor selection.
1) Who attends: Buyers / Attendees
Snowflake Summit brings together a dense concentration of enterprise buyers, technical practitioners, and ecosystem partners. The event is not just for end users; it also attracts teams that influence buying decisions across data, cloud, software, and business intelligence.
- Chief Data Officers, Chief Information Officers, Chief Technology Officers
- VPs and Directors of Data Engineering, Analytics, and Business Intelligence
- Cloud Architects, Solutions Architects, Data Platform Architects
- Data Engineers, Analytics Engineers, ML Engineers, and Platform Engineers
- Security, governance, privacy, and compliance leaders
- Product managers and digital transformation leaders
- Procurement and vendor management teams evaluating enterprise software
- Consultants, systems integrators, and implementation partners
- ISV partners, data app builders, and technology vendors
The strongest buyers are typically those evaluating data warehouse modernization, AI/ML enablement, data sharing, ETL/ELT tooling, cataloging, observability, governance, and enterprise reporting solutions.
2) Where the show is happening + attendee geographic origin
Snowflake Summit is usually hosted in a major U.S. convention destination with strong airlift and hotel capacity. The exact venue may change by year, but the event generally operates as a large-scale North American flagship conference with global pull.
Attendee origin:
- Primary: United States
- Secondary: Canada, United Kingdom, Western Europe, India, Singapore, Australia, and the Middle East
- Global reach: Strong international attendance from enterprise tech and partner ecosystems
Because Snowflake is a globally adopted cloud data platform, many attendees travel internationally to attend sessions, partner meetings, customer workshops, and executive networking.
3) Audience reach: Local / National / Global
Reach type: Global with strong North American concentration
This is not a local event. It has a global brand footprint and attracts attendees from multinational organizations, global consulting firms, software vendors, and data-driven enterprises. The biggest concentration still comes from the U.S., but the buyer quality is international.
4) Sample buyer company names + websites
Below are sample buyer accounts that are highly relevant for attendee-list targeting. These are the kinds of companies that usually attend, sponsor, exhibit, partner, or send internal decision-makers to this event.
| Priority | Company | Website | Best Title to Target | Why This is a Good Buyer Fit |
|---|---|---|---|---|
| 1 | Salesforce | salesforce.com | VP Data Engineering / Director, Analytics Platform / Cloud Architecture Leader | Large enterprise data and AI user base; strong need for scalable analytics, governance, and integration. |
| 2 | Uber | uber.com | Head of Data Platform / Director, BI Engineering / Staff Data Engineer | Data-intensive operations and strong demand for real-time analytics and experimentation platforms. |
| 3 | Adobe | adobe.com | VP Analytics / Director, Data Science Platform / Enterprise Data Architect | Deep analytics culture, digital experience data, and enterprise-scale cloud data workflows. |
| 4 | Intuit | intuit.com | Director, Data Engineering / VP, Analytics / Platform Engineering Manager | Strong data modernization, financial analytics, and AI-driven product development needs. |
| 5 | Capital One | capitalone.com | Director, Data Platform / Cloud Security Leader / Analytics Strategy Manager | Financial services company with major cloud, governance, and regulatory data requirements. |
| 6 | Netflix | netflix.com | Engineering Manager, Data Platform / Director, Machine Learning Infrastructure | Well-known for large-scale data use cases, personalization, and cloud-native analytics. |
| 7 | DoorDash | doordash.com | Head of Data Engineering / Analytics Engineering Lead / Product Analytics Director | High-volume transactional data and fast-moving business intelligence needs. |
| 8 | Atlassian | atlassian.com | Director, Data Platform / Head of Business Intelligence / Cloud Infrastructure Architect | Modern SaaS environment with strong collaboration, product analytics, and data engineering focus. |
| 9 | Visa | visa.com | Director, Enterprise Data / Analytics Security Manager / Data Governance Lead | Huge transaction volume and strong compliance, governance, and global reporting needs. |
| 10 | Walmart | walmart.com | VP Data & Analytics / Director, Retail Data Platform / Enterprise Data Architect | Retail scale, supply chain data, customer analytics, and omnichannel reporting. |
| 11 | Capital One | capitalone.com | Director, Cloud Data Engineering / Analytics Governance Manager | Repeated because of strong fit across banking analytics, risk, and platform modernization. |
| 12 | Siemens | siemens.com | Global Data Strategy Lead / Industrial Analytics Director | Industrial enterprise with large-scale operational and engineering data requirements. |
| 13 | PepsiCo | pepsico.com | Director, Enterprise Analytics / Supply Chain Data Leader | Strong use case for consumer analytics, demand planning, and operational dashboards. |
| 14 | Schneider Electric | se.com | Data Platform Manager / Digital Transformation Director | Industrial and energy data modernization with global business operations. |
| 15 | Accenture | accenture.com | Managing Director, Data & AI / Snowflake Practice Lead | Major consulting and implementation partner; strong buyer and ecosystem influence. |
| 16 | Deloitte | deloitte.com | Partner, Cloud Data & Analytics / Practice Lead, Data Modernization | High-value consulting buyer and influential services partner. |
| 17 | Infosys | infosys.com | Practice Head, Cloud Data Platforms / Delivery Leader, Analytics | System integrator with strong enterprise transformation exposure. |
| 18 | ServiceNow | servicenow.com | VP, Data Engineering / Director, Platform Analytics | Cloud platform company with strong operational analytics and enterprise customer data needs. |
| 19 | PayPal | paypal.com | Director, Data Science Platform / Analytics Engineering Manager | Financial technology company with high transactional data volumes and AI opportunities. |
| 20 | linkedin.com | Head of Data Platform / Director, Insights Engineering | Massive data and product analytics requirements make this a strong enterprise buyer fit. |
Top 5 best samples to send client first: Salesforce, Capital One, Accenture, Uber, Walmart. These names give a balanced mix of enterprise end users, financial buyers, consulting buyers, and large-scale data platform teams.
5) Job profiles, industries & event type
Best job profiles to target:
- Chief Data Officer
- Chief Information Officer
- Chief Technology Officer
- VP Data Engineering
- VP Analytics
- Director of Data Platform
- Director of Business Intelligence
- Head of Data Governance
- Cloud Solutions Architect
- Enterprise Architect
- Data Engineering Manager
- Analytics Engineering Manager
- Machine Learning Platform Lead
- Security and Compliance Director
- Digital Transformation Leader
- Partner / Practice Leader at consulting firms
Best industry filters to use from your industry list:
- Information Technology & Services
- Computer Software
- Computer Hardware
- Internet
- Information Services
- Financial Services
- Banking
- Insurance
- Management Consulting
- Professional Training & Coaching
- Market Research
- Telecommunications
- Retail
- Logistics & Supply Chain
- Manufacturing-related companies where data modernization is a priority
Event type: Enterprise technology conference, data platform summit, analytics and AI ecosystem event, partner and customer engagement conference.
6) Estimated attendance / expected footfall
Snowflake Summit typically draws a very large professional audience, especially because it combines end users, partners, developers, executives, and solution providers.
- Estimated total attendance: 10,000 to 20,000+ depending on location and year
- Buyer density: High
- Decision-maker concentration: Very high compared with general tech events
Footfall is strong, but the real value is quality over volume. Many attendees are directly involved in technology evaluation, product adoption, platform strategy, or vendor partnerships.
7) Key focus areas & buyer engagement
Core focus areas at this event:
- Data cloud strategy and modernization
- Enterprise analytics and BI
- AI and machine learning adoption
- Data governance, privacy, and compliance
- Data sharing and collaboration
- Real-time data pipelines and integration
- Observability, cataloging, and metadata management
- Security and access control
- Cloud migration and platform engineering
- Industry-specific use cases across finance, retail, healthcare, media, and software
Best buyer engagement strategy:
The best engagement is to position the attendee list around buyer intent rather than raw attendance. Strong messaging would emphasize access to data leaders, cloud architects, analytics managers, and enterprise technology evaluators. This event is ideal for organizations selling software, services, platforms, consulting, cloud tooling, security products, or enterprise data solutions.
For outreach, the highest-converting targets are usually:
- Companies already investing in cloud data transformation
- Consultancies and implementation partners
- Enterprise software companies with analytics use cases
- Financial services and retail brands with large-scale data operations
- Teams responsible for governance, AI adoption, and platform modernization
8) Client-product fit note
To recommend the best buyers with accuracy, I need your client website or product page. That allows me to map the event audience to the exact buying intent.
Examples:
- If your client sells data tooling, focus on data engineering, BI, and platform teams.
- If your client sells security or compliance software, focus on governance, risk, and cloud security leaders.
- If your client sells consulting services, target enterprise transformation leaders and consulting partners.
- If your client sells analytics or AI products, prioritize platform leaders, ML teams, and executive data sponsors.
- If your client sells cloud infrastructure or integration products, prioritize architects and engineering managers.
If you share the client website, I can refine this into a much sharper buyer list with titles, industries, company fit, and priority ranking.
9) Final recommendation
This is a strong event for attendee-list sales if your target market is enterprise technology, data, analytics, cloud, AI, or digital transformation. It is especially useful for identifying buyers with budget, platform responsibility, and technical influence.
Best buyer segments to collect:
- Data and analytics leadership
- Cloud architecture and platform engineering
- Security, governance, and compliance teams
- Consulting and systems integration firms
- Enterprise software buyers and partner teams
Quality rating for B2B attendee-list sales: 9/10
It is one of the strongest event types for high-value B2B prospecting because the audience is highly targeted, commercially relevant, and decision-maker heavy.
Data sheet
| Event Name | Snowflake Summit |
| Event Date | 1 June 2026 to 4 June 2026 |
| Event Status | Upcoming |
| Venue | San Francisco, California, USA (official venue details should be verified on the event registration page) |
| City | San Francisco |
| State / Region | California (CA) |
| Country | United States |
| Organizer | Snowflake Inc. |
| Official Event Website | summit.snowflake.com |
| Event Type | Data cloud, analytics, AI/ML, data engineering, platform engineering, security, modern data stack, enterprise technology |
| Primary Category | IT & Technology |
| Secondary Applicable Categories | Business Services; Science & Research |
| Audience Reach | Global, with strong North American enterprise concentration |
| Estimated Attendance / Expected Footfall | Attendance figure not publicly confirmed by the organizer. |
| Attendance Data Reliability | Medium. Event scale is clearly enterprise-grade, but current-year attendance has not been publicly confirmed in the available official materials reviewed here. |
| Main Purpose of Event | To showcase Snowflake’s platform roadmap, data and AI use cases, customer success stories, ecosystem partnerships, and enterprise data modernization strategies. |
Snowflake Summit is a flagship enterprise technology conference focused on data cloud architecture, analytics modernization, AI adoption, governance, security, and application development on the Snowflake platform. It brings together technical teams and business decision-makers who are actively evaluating data infrastructure, cloud-native analytics, and scalable AI-enabled workflows.
The event matters because it sits at the center of enterprise data spending and vendor evaluation. Attendees typically include data platform owners, engineering leaders, analytics executives, security and governance teams, and ecosystem partners who influence procurement, implementation, and renewal decisions. For B2B lead generation, this is a high-intent event for organizations selling cloud software, data tools, consulting, integration services, security, and enterprise transformation offerings.
| Buyer / Attendee Segment | Typical Organizations | Buying Role or Influence | Relevance to Exhibitors / Suppliers |
|---|---|---|---|
| Data Platform Teams | Enterprise, mid-market, and digital-native companies | Evaluate data stack architecture, platform fit, and scaling needs | High-value audience for data tooling, integrations, governance, and services |
| Procurement and Sourcing Teams | Large enterprises, public sector, regulated industries | Support software selection, contract negotiation, renewal management | Important for vendor qualification, budget cycles, and enterprise sales |
| CIO / CTO / IT Leadership | Large enterprises, software companies, regulated firms | Own platform direction, transformation priorities, and major buy decisions | Ideal audience for enterprise account-based outreach |
| Chief Data Officers / Data Executives | Enterprise data-driven organizations | Set data strategy, governance, monetization, and modernization priorities | Strong buyers for analytics, governance, MDM, data sharing, AI platforms |
| Data Engineering / Platform Engineering | Technology, fintech, retail, healthcare, manufacturing | Influence build-versus-buy, architecture choices, implementation tools | High relevance for ETL/ELT, orchestration, observability, DevOps tools |
| Analytics / BI Leaders | Retail, CPG, finance, healthcare, SaaS | Evaluate self-service BI, dashboards, data access, and performance | Useful for BI, semantic layer, and reporting vendors |
| Security / Governance / Compliance | Regulated and global enterprises | Review controls, access management, risk, and data policy | Relevant for data security, privacy, and compliance solutions |
| Systems Integrators / Consultants | Global SIs, boutique data consultancies, MSPs | Recommend and implement platforms across client accounts | Strong channel, partnership, and services opportunities |
| Product / Data Product Leaders | SaaS and digitally enabled enterprises | Own data products, embedded analytics, customer-facing data use cases | Relevant for data sharing, monetization, app and marketplace plays |
| Operations / Finance / RevOps Leaders | Enterprise and scale-up organizations | Need trusted data for forecasting, reporting, and cross-functional visibility | Potential buyers for analytics, planning, and data quality tools |
| Geographic Area | Likely Attendee Origin | Buyer Concentration | Notes |
|---|---|---|---|
| Host City: San Francisco | High | High | Strong concentration of tech buyers, investors, and enterprise decision-makers. |
| Host State / Region: California | Very High | High | Large base of cloud software, AI, media, retail, and enterprise technology buyers. |
| Nearby Business Hubs | San Jose, Palo Alto, Mountain View, Oakland, Seattle, New York | High | Likely draw from major technology and enterprise buyer hubs. |
| National Reach | Very High | Very High | Enterprise data initiatives are nationwide across US industries. |
| International Reach | High | Medium to High | Global customers, partners, and technical users are likely to attend. |
| Key States / Regions | California, New York, Texas, Washington, Illinois, Massachusetts | High | Major enterprise buying centers and technology corridors. |
| Reach Level | Assessment | Explanation |
|---|---|---|
| Global | Primary classification | Snowflake Summit is a flagship international enterprise technology event with broad multinational relevance and strong ecosystem participation. |
| Buyer Company / Organization | Buyer Type | Why It Is Relevant | Website | Best Job Titles to Target | Evidence Level |
|---|---|---|---|---|---|
| Adobe | Enterprise software buyer | Large-scale data, analytics, and AI workflows are strategically relevant. | adobe.com | CIO, VP Data, Director of Analytics, Data Platform Lead | Strong Market Fit, Attendance Not Confirmed |
| Capital One | Financial services buyer | Data governance, cloud modernization, and analytics are core priorities. | capitalone.com | Chief Data Officer, VP Procurement, Director of Data Engineering | Strong Market Fit, Attendance Not Confirmed |
| Deloitte | Consulting / services buyer | Often advises clients on data cloud strategy and implementation. | deloitte.com | Managing Director, Partner, Cloud Practice Lead, Data Transformation Lead | Strong Market Fit, Attendance Not Confirmed |
| Walmart | Retail buyer | Retail analytics, supply chain visibility, and data sharing are major use cases. | walmart.com | VP Data, Director of Supply Chain Analytics, Procurement Manager | Strong Market Fit, Attendance Not Confirmed |
| Nike | Retail / consumer brand buyer | Enterprise analytics and product data operations are highly relevant. | nike.com | Director of Data Engineering, Analytics Director, IT Director | Strong Market Fit, Attendance Not Confirmed |
| UnitedHealth Group | Healthcare buyer | Healthcare data modernization, reporting, and compliance are major priorities. | uhg.com | Chief Data Officer, VP Analytics, Data Governance Leader | Strong Market Fit, Attendance Not Confirmed |
| Salesforce | Technology buyer / platform ecosystem | Common enterprise data and AI integration stakeholder. | salesforce.com | VP Platform, Product Analytics Lead, Enterprise Architect | Strong Market Fit, Attendance Not Confirmed |
| T-Mobile | Telecommunications buyer | Large telecom operators depend on scalable analytics and governance. | t-mobile.com | VP Data Strategy, IT Director, Director of Business Intelligence | Strong Market Fit, Attendance Not Confirmed |
| General Mills | Food / CPG buyer | Demand forecasting, supply chain analytics, and enterprise reporting are relevant. | generalmills.com | Supply Chain Director, Analytics Director, Procurement Leader | Strong Market Fit, Attendance Not Confirmed |
| FedEx | Logistics / transportation buyer | Operational analytics, network performance, and data integration are key needs. | fedex.com | VP Operations Analytics, CIO, Data Platform Manager | Strong Market Fit, Attendance Not Confirmed |
| Sony | Global enterprise buyer | Cross-border data, analytics, and digital transformation are relevant. | sony.com | IT Director, Data Governance Lead, Enterprise Architecture Head | Strong Market Fit, Attendance Not Confirmed |
| NASA | Government / research buyer | Data-intensive mission, research, and analytics environments align with the event theme. | nasa.gov | Program Manager, IT Director, Data Architect | Strong Market Fit, Attendance Not Confirmed |
| Priority | Job Title / Function | Department | Seniority Level | Why This Role Matters |
|---|---|---|---|---|
| 1 | Chief Data Officer | Data / Analytics | C-Level | Owns enterprise data strategy, governance, and platform investment. |
| 2 | VP Data / Analytics | Data / Analytics | VP | Defines tools, roadmaps, and vendor selection for analytics modernization. |
| 3 | Director of Data Engineering | Engineering / Data Platform | Director | Influences ETL/ELT, warehousing, pipelines, and platform integration. |
| 4 | Director of Analytics / BI | Analytics / BI | Director | Responsible for reporting, insights delivery, and self-service analytics. |
| 5 | CIO / CTO | IT Leadership | C-Level | Owns platform standards, cloud investment, and enterprise transformation priorities. |
| 6 | Procurement Manager / Strategic Sourcing Manager | Procurement | Manager / Senior Manager | Supports software evaluation, commercial negotiations, and vendor risk review. |
| 7 | Data Governance Lead / Privacy Lead | Governance / Compliance | Manager / Director | Key stakeholder for access control, policy, and audit readiness. |
| 8 | Enterprise Architect / Platform Architect | Architecture / IT | Senior Manager / Director | Evaluates interoperability, scalability, and stack design. |
| 9 | Solutions Architect / Cloud Architect | Engineering / Cloud | Senior IC / Manager | Often the technical evaluator and implementation gatekeeper. |
| 10 | Product Analytics / Data Product Manager | Product / Analytics | Manager / Director | Needs reliable data for product, customer, and monetization decisions. |
| Priority | Apollo Industry | Why It Fits the Event | Best Buyer Use Case |
|---|---|---|---|
| 1 | Information Technology & Services | Core industry for cloud, data, and platform decision-makers. | Enterprise platform buying and digital transformation |
| 2 | Computer Software | High concentration of technical evaluators and platform buyers. | Data platform, BI, and AI tooling |
| 3 | Financial Services | Large regulated buyers of secure analytics and governance solutions. | Risk, compliance, reporting, AI governance |
| 4 | Retail | Strong use cases for merchandising, supply chain, customer analytics. | Demand forecasting, BI, omnichannel analytics |
| 5 | Health, Wellness & Fitness | Health systems and digital health organizations need governed data workflows. | Healthcare analytics and interoperability |
| 6 | Hospital & Health Care | Clinical, operational, and claims data modernization are top priorities. | Data governance, reporting, secure sharing |
| 7 | Telecommunications | Network-scale analytics and customer intelligence are common needs. | Operational analytics and AI applications |
| 8 | Logistics & Supply Chain | Data-driven operations and forecasting are important buying triggers. | Supply chain visibility and optimization |
| 9 | Marketing & Advertising | Customer data platforms and attribution analytics are highly relevant. | CDP, BI, audience analytics |
| 10 | Management Consulting | Consultancies influence client platform selection and implementation. | Channel, referral, and co-sell opportunities |
| Metric | Figure | Status | Source / Basis | Notes |
|---|---|---|---|---|
| Estimated total footfall | Not publicly confirmed | Confirmed absence of public number | Official materials reviewed did not disclose a current-year figure | Use only organizer-confirmed data if obtained later. |
| Exhibitor count | Not publicly confirmed | Unconfirmed | Requires official exhibitor directory or prospectus | Current-year exhibitor count should be checked on summit.snowflake.com. |
| Buyer count | Not publicly confirmed | Unconfirmed | No current-year buyer list publicly verified in reviewed materials | High likelihood of enterprise buyer presence, but not countable without organizer data. |
| Speaker count | Not publicly confirmed | Unconfirmed | Agenda and speaker roster should be used for validation | Useful for confirmed speaker-org prospecting once list is published. |
| Sponsor count | Not publicly confirmed | Unconfirmed | Event sponsorship pages / prospectus needed | Sponsor ecosystem is typically substantial for Snowflake Summit. |
| Historical attendance | Not used here | Historical / prior-year evidence only | Prior-year official event materials may contain figures | Avoid using unverified numbers in outreach materials. |
| Focus Area | Typical Buyer Need | Buyer Engagement Opportunity | Relevant Supplier Offering |
|---|---|---|---|
| Data Platform Modernization | Consolidate data systems and reduce complexity | Architecture review, migration planning, proof-of-value demos | Cloud data platforms, migration services, architecture consulting |
| AI / ML Enablement | Operationalize AI on trusted data | Use-case workshops, data readiness assessments | ML platforms, feature stores, AI governance tools |
| Security / Governance | Protect sensitive data and meet compliance obligations | Risk and compliance conversations with technical and executive stakeholders | Data security, masking, policy, access control, audit tooling |
| Analytics / BI | Improve insights access and decision speed | Executive dashboards and self-service analytics demos | BI, semantic layer, reporting, data catalog tools |
| Data Sharing / Monetization | Externalize and commercialize data assets | Partnership and marketplace discussions | Data sharing platforms, marketplaces, API services |
| Cloud Cost / FinOps | Control spend while scaling workloads | ROI and savings-led outreach | FinOps, workload optimization, observability |
| Factor | Assessment | Explanation |
|---|---|---|
| Buyer relevance | Very High | The event attracts exactly the kinds of data, cloud, analytics, and transformation buyers that many B2B suppliers want. |
| Decision-maker availability | High | Strong mix of executives, directors, architects, and technical evaluators. |
| Data collection potential | High | Once attendee, speaker, or sponsor rosters are available, the list-building potential is strong. |
| Apollo targeting potential | Very High | Apollo can efficiently target industries, seniority, titles, geographies, and company sizes aligned to this audience. |
| Geographic targeting potential | High | The San Francisco location is ideal for West Coast enterprise and tech-account targeting, plus national accounts. |
| Best outreach approach | High-touch ABM + event-triggered outreach | Target by account list, role, and event theme; align messaging to current data/AI modernization priorities. |
| Overall lead quality | Very High | One of the strongest enterprise technology events for data and AI buyer intelligence. |
| Best use case | Attendee list sales, account-based prospecting, partner targeting, and enterprise pipeline generation | Best suited for firms selling data infrastructure, cloud software, implementation, analytics, and governance solutions. |
| Limitations / risks | Limited public attendee data | Current-year attendance and attendee list details may not be publicly available before the event. |
| Filter Type | Recommended Filters | Purpose |
|---|---|---|
| Apollo industries | Information Technology & Services; Computer Software; Financial Services; Retail; Hospital & Health Care; Telecommunications; Logistics & Supply Chain; Management Consulting | Prioritize industries most likely to buy data, analytics, and cloud solutions. |
| Departments | Information Technology; Engineering; Data & Analytics; Procurement; Operations; Product; Security | Focus on functional owners and evaluators. |
| Seniority | Manager; Director; VP; CXO; Head | Capture both decision-makers and active platform influencers. |
| Job titles | Chief Data Officer; VP Data; Director of Data Engineering; Director of Analytics; CIO; CTO; Enterprise Architect; Cloud Architect; Procurement Manager; Strategic Sourcing Manager; Data Governance Lead | Match direct buying roles and technical evaluators. |
| Geography | United States; California; West Coast metros; New York; Texas; Washington; Illinois; Massachusetts; UK; Canada; Singapore | Target enterprise markets with strong cloud and data-spend density. |
| Employee size | 201-500; 501-1,000; 1,001-5,000; 5,001-10,000; 10,000+ | Best fit for enterprise and upper mid-market deal sizes. |
| Keywords | data cloud; analytics; Snowflake; data engineering; AI; machine learning; governance; modern data stack; data platform; BI; cloud migration | Find teams already investing in aligned initiatives. |
| Technologies | Snowflake; AWS; Azure; Databricks; dbt; Tableau; Power BI; Looker; Kafka; Spark | Useful if prospecting around stack adjacency or migration opportunities. |
| Company type | Enterprise; Scale-up; Regulated enterprise; Systems integrator; Consulting firm | Prioritize organizations with active transformation budgets. |
| Revenue range | $50M+ where applicable; highest priority at $500M+ | Aligns with enterprise-scale buying behavior. |
| Source | Type | What It Verified | Reliability |
|---|---|---|---|
| Snowflake Summit Official Website | Official organizer site | Event brand, theme, positioning, and official event landing page | High |
| Snowflake Summit Event Information Page | Official organizer page | Event positioning, audience relevance, and conference scope | High |
| Snowflake Newsroom / Press Releases | Official company source | Corporate event announcements, product themes, and ecosystem context | High |
| Snowflake Customer Stories | Official company source | Industry relevance and common buyer profiles across sectors | High |
| Moscone Center | Venue website | San Francisco venue context and location verification support | Medium to High |
| Eventscribe / Event Directory Reference | Event platform reference | Typical use for agendas, exhibitor directories, and speaker listings when published | Medium |
| Snowflake LinkedIn Company Page | Corporate social profile | Additional confirmation of organizer identity and market positioning | Medium |
🎯 Selling to this event's audience? Get a free tailored buyer list
Tell us your work email and our AI instantly builds a buyer list matched to Snowflake Summit — the best‑fit companies to target, the exact decision‑maker job titles, and the industry filters that fit what you sell.
