Industry Architect – Advertising & Media

About the role

As an Industry Architect within the Industry and Data/AI Architect teams at Snowflake, you will be a trusted technical partner driving industry-specific transformation. Your goal is to help customers unlock measurable business value by adopting and building on Snowflake’s AI Data Cloud. Specifically, you will serve as the technical visionary for Advertising & Media, focusing on the buy-side and measurement ecosystem.

Responsibilities

• Partner with Brands & Agencies on Strategic Opportunities
• 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.
• Innovate and Design Marketing Effectiveness & Measurement Solutions
• 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.
• Drive Repeatability and Scale
• 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.
• 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.
• Influence the Product Roadmap
• 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.
• Be a Thought Leader for the Advertising & Media Industry
• 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.

Requirements

• Buy-Side / Measurement Ecosystem Background: 10+ years in architecture, marketing science, or technical consulting roles within the advertising and media ecosystem, with specific experience on the buy-side.
• Deep Expertise in Media Measurement & Marketing Science: 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.
• Knowledge of the Privacy & Identity Landscape: 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.
• Technical Proficiency (Hands-On): 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.
• Data Science Fluency for Advertising & Marketing: 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.
• Executive And Storytelling Skills: 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.

Qualifications

• 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.