Note: The job is a remote job and is open to candidates in USA. Snowflake is empowering enterprises to achieve their full potential by seeking AI-native thinkers across every function. The Industry Architect for Advertising & Media will drive industry-specific transformation by partnering with global brands and media agencies to unlock measurable business value through Snowflake’s AI Data Cloud.
Responsibilities
- Drive engagement with the world’s largest advertisers and agency holding companies across brand, performance, and advanced analytics teams
- Build trusted relationships with Chief Data Officers, CMOs, Heads of Analytics/Marketing Science, and Enterprise Architects, acting as the bridge between media strategy, marketing science, and technical implementation
- Help customers re-architect how they plan, measure, and optimize media investments using Snowflake
- Translate complex advertising and marketing questions such as signal loss, cross-channel attribution, incrementality, reach and frequency, audience quality, and business lift into data-driven architectures and analytical frameworks
- Design end-to-end blueprints for Media Mix Modeling (MMM), Multi-Touch Attribution (MTA), incrementality testing, and unified measurement using Snowflake, Python, and modern ML techniques
- Architect solutions that leverage Data Clean Rooms, privacy-enhancing technologies, identity resolution, and AI/ML to connect exposure, consumer, and outcome data in a privacy-safe way
- Lead strategic initiatives by creating repeatable solution assets, such as: Marketing effectiveness and MMM frameworks that connect media impressions to sales and business KPIs
- Audience and identity architectures that unify first-party, partner, and platform data
- Commerce/Retail Media Network blueprints when relevant to advertisers and their partners
- Simulation, optimization, and scenario-planning solutions that help clients test investment strategies against business goals before activation
- Help shape new solution concepts from idea to prototype to customer validation, working closely with data scientists, engineers, and product teams to bring new measurement and optimization capabilities to market
- Build demo showcases and reference implementations that prove how AI agents, automation, advanced analytics, and SaaS-style analytical workflows can transform media planning, optimization, and reporting
- Act as the voice of the advertiser and marketing science leader to Snowflake’s product engineering teams
- Provide structured feedback on the specific needs of marketers and analytics leaders, including: Privacy and governance controls, Statistical and modeling workflows for MMM and incrementality, Non-technical user experiences for marketers and media teams
- Drive technical thought leadership in marketing science and media measurement for the Advertising & Media industry
- Author technical blogs, reference architectures, and best practices on topics such as MMM, MTA, unified measurement, marketing mix optimization, and data clean rooms
- Speak at major industry and analytics events (e.g., IAB, ANA, Cannes Lions, AdWeek, POSSIBLE, Gartner Analytics & Measurement, MAICON) and lead field enablement to upskill the sales organization and partner ecosystem
- Help major brands and agencies understand how peers are adopting the AI Data Cloud for marketing and media
- Show how Snowflake solves for fragmented media, consumer, and outcome data to support modern marketing science and measurement
- Move customers from legacy, opaque “black box” measurement to transparent, data-driven frameworks that the brand owns and understands
- Design architectures that unify media, commerce, CRM, and outcome data in a governed, privacy-safe environment
- Determine how customers should integrate with DSPs, SSPs, measurement partners, and identity providers (e.g., LiveRamp, The Trade Desk, leading MMM/MTA and analytics platforms)
- Facilitate technical alignment between the customer, Snowflake, and the broader Advertising & Media ecosystem, including measurement and analytics partners
- Design architectures for: Retail and Commerce Media Networks (RMNs) and co-op media models
- Measurement frameworks that connect media, consumer journeys, and business outcomes
- Privacy-safe collaboration between brands, agencies, publishers, and partners
- Ensure customer architectures are compliant with privacy regulations (GDPR, CCPA, and others) and consent requirements while maximizing analytical utility and flexibility
- Establish long-running relationships with Brand and Agency leadership to maintain a consistent vision across global business units and regions
- Act as a long-term advisor on how to evolve marketing science, media measurement, and data collaboration using Snowflake
- Drive strong alignment with the Marketing & Advertising Industry GTM, Product Marketing, and Alliances teams so that Snowflake shows up with a unified narrative in the market
- Develop and maintain a clear point of view on industry trends such as data clean rooms, identity, data mesh, GenAI, and the evolution of linear and digital measurement
- Frame these trends through an advertiser and marketing science lens, including case studies, implementation patterns, and tradeoffs
- Bring in the wider Snowflake team to run hands-on labs, solution workshops, and Snowdays focused on measurement, marketing science, and media optimization
- Complement the customer’s point of view with broader industry perspectives and practical solution patterns
- Provide industry and marketing science expertise in RFPs and strategic pursuits that require deep knowledge of: The advertising supply chain and buying workflows, Audience creation, activation, and measurement, Methodological choices and their impact on business outcomes
Skills
- 10+ years in architecture, marketing science, or technical consulting roles within the advertising and media ecosystem, with specific experience on the buy-side: Enterprise brands, media agencies, or consulting firms serving them or Adtech, measurement/currency, or analytics companies implementing solutions directly with media buyers and marketing leaders
- Strong grasp of media and marketing measurement methodologies, including: Media Mix Modeling (MMM) and budget optimization, Multi-Touch Attribution (MTA) and identity/attribution models, Incrementality and lift studies (geo experiments, holdouts, causal inference), Reach & frequency, audience quality, and outcome-based KPIs
- Experience leading or guiding marketing science teams that own these models and explain their business impact to executives
- Sophisticated understanding of the transition away from third-party cookies and device IDs
- Hands-on familiarity with: Data Clean Rooms (DCRs) and collaboration patterns, Privacy Enhancing Technologies (PETs), Identity resolution and use of identity providers, clean room partners, and platform IDs
- Strong knowledge and experience with SQL and Python for building analytic data sets, running models, and operationalizing measurement workflows
- Experience working within cloud environments (AWS, Azure, GCP) and their services
- Ability to review and guide data models, pipelines, and analytics code with both internal teams and customer data/analytics groups
- Understanding of how Machine Learning and Generative AI apply to advertising and marketing, including: Propensity and response modeling, Churn and lifetime value prediction, Audience and lookalike modeling, Budget allocation, scenario planning, and optimization
- Comfort explaining model design, tradeoffs, and limitations to non-technical stakeholders and aligning them to business outcomes
- Experience in a customer-facing role with the ability to: Whiteboard complex, end-to-end architectures for CTOs, CMOs, and Heads of Marketing Science, Translate those architectures into clear narratives about business value, risk, and impact on media ROI
- A Bachelor's degree in computer science, engineering, statistics, mathematics, economics, or a related field is required
- A Master's degree (or equivalent advanced degree) in a quantitative or business discipline is preferred
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