Principal Consultant (Martech)
4 days ago
Paris
PRINCIPAL CONSULTANT - Marketing Technology (MarTech) Domain Role Summary The Principal Consultant, MarTech Domain leads strategy consulting engagements that help clients design, rationalize, implement, and extract value from their marketing technology ecosystems. This role spans strategy through execution: from MarTech vision and stack architecture to vendor selection, implementation governance, data strategy, AI capability integration, and change management. The role carries dual accountability — as a senior client advisor who owns relationships and engagement quality, and as a domain champion who builds and evolves the practice's MarTech methodology, intellectual capital, and go-to-market positioning. This is a high-visibility, high-impact position that directly shapes both client outcomes and practice growth. Key Responsibilities Client Advisory & Engagement Leadership • 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., • Go-to-Market Support: Partner with business development to shape and pursue MarTech-domain opportunities: contribute to proposals, RFP responses, and client pitches; represent the practice at industry events and partner ecosystems (Adobe, Salesforce, Google)., • Talent Development: Coach and mentor consultants on MarTech domain knowledge, client engagement techniques, AI tool usage, and platform expertise; contribute to practice hiring and capability planning. Qualifications Experience • 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. MarTech & AI Expertise • 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. Consulting & Leadership Skills • Exceptional strategic thinking and structured problem-solving; able to frame complex MarTech challenges into clear, executive-level narratives and business cases., • Outstanding communication and presentation skills; experienced presenting to and influencing C-suite marketing and technology executives., • Strong business case development capability — able to model and articulate ROI of MarTech investments, platform migrations, and AI capability adoption., • Proven ability to lead and inspire multidisciplinary teams across strategy, analytics, technology, and creative disciplines., • Motivated self-starter and continuous learner; actively tracks MarTech vendor landscape evolution, AI capability releases, and industry analyst perspectives (Gartner, Forrester, Scott Brinker's MarTech landscape)., • 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.
