Responsibilities

• MarTech Strategy & Vision: Lead engagements that define clients' MarTech north star: assessing current-state stack maturity, identifying capability gaps, and designing a prioritized technology and operating model roadmap aligned to business strategy and customer experience goals.
• Stack Rationalization & Architecture: Guide clients through MarTech stack audits and consolidation decisions — evaluating platform sprawl, redundancy, integration complexity, and total cost of ownership to recommend a coherent, scalable architecture.
• Vendor Selection & RFP Leadership: Lead structured vendor evaluation and selection processes for marquee MarTech platforms (CDP, MAP, CRM, CMS, personalization); develop evaluation frameworks, scoring models, and executive recommendation packages.
• Engagement Ownership: Own the full engagement plan: scope, milestones, team structure, risk management, client communication, and delivery quality. Serve as primary client point of contact and trusted advisor throughout.
• Stakeholder Management: Build and sustain relationships with CMOs, VPs of Marketing, CIOs, and Digital leaders; translate marketing strategy imperatives into technology investment decisions with clear business case justification.
• AI-Driven Marketing & Personalization: AI Marketing Strategy: Advise clients on integrating AI capabilities into their marketing operations: predictive lead scoring, AI-driven audience segmentation, next-best-action engines, generative content at scale, and automated campaign optimization.
• Generative AI in Marketing: Lead advisory engagements on GenAI adoption for marketing — content generation workflows, brand governance guardrails, creative automation, AI-assisted email and journey personalization — helping clients move from experimentation to production at scale.
• Agentic Marketing Capabilities: Identify and guide implementation of emerging agentic AI applications in marketing: autonomous campaign management, AI-orchestrated customer journeys, and AI-powered real-time decision engines integrated with MarTech platforms.
• Personalization & CX Architecture: Design omnichannel personalization strategies — connecting CDP, CMS, personalization engine, and analytics into a unified customer intelligence and activation loop across web, mobile, email, and in-store touchpoints.
• Responsible AI in Marketing: Embed responsible AI principles into all AI marketing advisory: consent architecture, data privacy compliance (GDPR, CCPA), bias in targeting and messaging, transparency in AI-driven decisions, and ethical use of customer data.
• Data Strategy & Customer Intelligence: Customer Data Architecture: Advise on first-party data strategy in a cookieless, privacy-first world: defining data collection, identity resolution, enrichment, segmentation, and activation architectures that respect consent and maximize data utility.
• MarTech Data Integration: Design integration architectures connecting MarTech platforms to enterprise data infrastructure — data warehouses, CDPs, BI layers, and API ecosystems — ensuring clean, unified customer data flows across the stack.
• Measurement & Attribution: Define marketing measurement frameworks: multi-touch attribution models, incrementality testing, media mix modeling, and AI-assisted analytics to connect marketing investment to business outcomes.
• Data Clean Rooms & Identity: Guide clients on privacy-safe data collaboration strategies, data clean room architectures, and identity resolution approaches as third-party cookies deprecate and walled gardens grow.
• Implementation Governance & Change Management: Implementation Strategy: Develop phased implementation roadmaps for MarTech platforms, balancing speed-to-value with integration complexity, change capacity, and business priority — including build-buy-partner decisions.
• Program Governance: Establish governance frameworks for large-scale MarTech programs: steering cadences, workstream interdependency management, risk registers, and vendor management protocols.
• Organizational Design & Enablement: Advise on MarTech operating model design — team structures, roles, CoE models, agency vs. in-house decisions — and develop enablement plans that build internal capability alongside platform adoption.
• Change Management: Lead change management strategies for MarTech transformations, ensuring adoption by marketing, digital, IT, and data teams; develop training plans, communication strategies, and success metrics.
• Practice Development & Thought Leadership: MarTech Practice IP: Build and maintain the practice's MarTech intellectual capital: platform evaluation frameworks, stack architecture blueprints, AI marketing maturity models, vendor comparison tools, and engagement delivery accelerators.
• Thought Leadership: Author POVs, case studies, and market perspectives on MarTech trends — AI-native marketing, composable stacks, data clean rooms, cookieless futures, agentic marketing — for client and market-facing publication.

Requirements

• 10+ years of professional experience in consulting, marketing technology, or digital marketing roles.
• Minimum 5 years in a senior advisory or implementation leadership capacity directly within the MarTech domain.
• Demonstrated track record leading complex MarTech engagements — stack strategy, platform selection, implementation governance, and operating model design — for enterprise clients.
• Deep hands-on familiarity with two or more tier-1 MarTech platforms (e.g., SFMC, Adobe Experience Cloud, HubSpot Enterprise, Segment, AEM) — sufficient to lead architecture discussions, challenge vendor claims, and guide implementation decisions.
• Cross-industry experience preferred; retail, financial services, healthcare, CPG, and/or B2B SaaS exposure particularly valuable.
• Experience working at or alongside CMO/CDO/CTO functions; understands both marketing strategy and technology delivery realities.
• Comprehensive knowledge of the modern MarTech ecosystem across customer data, marketing automation, personalization, CMS, analytics, DAM, and eCommerce.
• Hands-on experience advising on or implementing AI-driven marketing capabilities: predictive audiences, GenAI content, recommendation engines, AI-assisted journey orchestration.
• Working knowledge of customer data architecture: CDPs, identity resolution, first-party data strategy, consent management, data clean rooms, and cookieless marketing approaches.
• Fluency with generative AI tools (Claude, ChatGPT, Copilot, Adobe Firefly, Jasper, Writer, or similar) used both for consulting delivery acceleration and as advisory subject matter.
• Familiarity with marketing analytics, attribution modeling, and data visualization tools; ability to engage credibly on measurement strategy.
• Understanding of API integration patterns, composable architecture, and headless/MACH principles as they apply to MarTech stack design.
• Bachelor's degree in Business, Marketing, Computer Science, or related field required; MBA or relevant postgraduate degree highly preferred.
• Relevant certifications valued: Salesforce Marketing Cloud, Adobe Experience Cloud, Google Analytics, HubSpot, CDP Institute, or AI/ML certifications.
• Willingness and ability to travel 50%+ to client locations based on engagement requirements.

Nice To Have

• MBA or relevant postgraduate degree highly preferred.

Benefits

• Medical, vision, and dental benefits, 401k retirement plan, variable pay/incentives, paid time off, and paid holidays are available for full time employees.