Sales Engineer, Data

Sales Engineer, Data

This is a consultative sales engineering opportunity focused on helping enterprise clients solve complex challenges through advanced data and technology solutions. You'll serve as the technical and data authority throughout the sales process, partnering closely with commercial teams and senior client stakeholders. The role combines technical discovery, solution design, data expertise, demonstrations, pilots, and strategic advisory work. You'll engage with leading brands, agencies, and media organizations to understand their environments and translate business needs into credible solutions. Your expertise will span data architecture, identity, privacy, activation, modeling, and AI-powered marketing technologies. With significant autonomy, you'll influence both individual deals and the evolution of the underlying product and data offering. This is an ideal role for a curious, commercially minded technical professional who enjoys turning complex data challenges into compelling business outcomes.

Accountabilities:

• Lead technical discovery with prospects, developing a deep understanding of their business objectives, data environments, technical requirements, and measures of success before recommending solutions.
• Scope and design solutions aligned with client requirements, collaborating with internal teams to determine the capabilities and resources needed to successfully deliver each opportunity.
• Own the technical response to RFPs and RFIs, ensuring proposed solutions are accurate, compelling, and aligned with client priorities.
• Act as a trusted technical advisor to senior marketing, insights, commercial, and other business stakeholders, translating technical concepts and trade-offs into clear business decisions.
• Build and deliver high-quality technical presentations, demonstrations, briefings, and working sessions covering platform capabilities, data, architecture, methodology, and relevant use cases.
• Engage directly with senior stakeholders at brands, agencies, and media organizations through both remote and in-person meetings.
• Lead pilots, proof-of-concepts, and technical data testing initiatives, including subsequent data assessment and implementation engagements.
• Advise clients and prospects on key data topics such as privacy, identity, attribution, and data activation.
• Represent the organization's technical and data perspective at client meetings, industry events, trade publications, and other relevant forums.
• Capture client feedback, requirements, and platform enhancement opportunities and communicate them effectively to Research and Product teams.
• Maintain strong relationships across internal teams and contribute to the development of technical knowledge and reusable best practices.
• Manage the technical direction of assigned opportunities with a high degree of ownership and autonomy.

Requirements:

• Approximately 5+ years of experience in technical pre-sales, sales engineering, solutions architecture, or a closely related role, ideally involving data, identity, analytics, or modeling.
• Demonstrated consultative approach to sales engineering, with the ability to lead discovery, diagnose underlying business problems, and design solutions rather than simply deliver product demonstrations.
• Working knowledge of the adtech, martech, and broader data ecosystems.
• Strong understanding of privacy regulations and best practices related to the handling and use of first-party data.
• Deep familiarity with data append delivery processes, including file matching, match rates, and associated client discussions.
• Strong understanding of data concepts including data lakes, APIs, MCP (Model Context Protocol), PII handling, identity resolution, and downstream data activation endpoints.
• Ability to quickly understand complex proprietary datasets and communicate their value to both technical and business audiences.
• Proven ability to establish credibility with senior marketing, insights, and commercial stakeholders, supported by excellent presentation, communication, and writing skills.
• Strong ability to explain complex technical subjects clearly and connect technical decisions to commercial outcomes.
• Comfortable working independently with significant autonomy in a growth-stage environment.
• Hands-on experience with Snowflake, AWS, Box, or activation platforms such as The Trade Desk, Adobe, Google, and Meta is a strong advantage.
• Understanding of data science techniques and modeling best practices is preferred.
• Experience with marketing analytics, data enhancement, marketing automation, syndicated research, or media technology is beneficial.
• Familiarity with the martech vendor ecosystem, particularly DSPs, DMPs, and data providers, is a plus.
• Bachelor's degree in computer science, engineering, statistics, business, or a related field is preferred; equivalent practical experience is also valued.
• Curious, proactive, accountable, adaptable, collaborative, customer-focused, and comfortable challenging assumptions when doing so creates better outcomes.

Benefits:

• Competitive compensation: Opportunity for strong earning potential with uncapped growth potential.
• Remote-first work: Flexible working environment designed to support collaboration across locations.
• Flexible workplace options: Work remotely or use available office environments when in-person collaboration is valuable.
• Comprehensive benefits: Benefits designed to support employees and their families, with full details shared during the hiring process.
• 401(k) plan: Competitive employer matching to support long-term financial planning.
• Flexible time off: Open PTO policy designed to encourage meaningful time away from work.
• Professional impact: Opportunity to directly influence revenue, product development, and client outcomes without requiring people management.
• Cutting-edge technology: Work with AI-powered marketing data, identity, analytics, and technology solutions.
• Varied client exposure: Engage with brands, agencies, and media organizations across a diverse range of business challenges.
• Professional development: Opportunity to contribute to industry conversations, events, thought leadership, and internal knowledge sharing.
• Collaborative environment: Work alongside experienced professionals across sales, research, product, and technology functions.
• Travel opportunities: Occasional travel for client meetings, industry events, and intentional in-person collaboration.