Director – Data Strategy - Data Products & Activation

The Opportunity

Marketing is transforming how it turns data into growth. At the center of that transformation is ourMarTech, AI & Data Strategy team — the group that owns the platforms, data, and AI capabilities that power modern marketing. We are building one trusted, governed, AI-ready data foundation so that every marketer, model, and campaign draws from a single version of truth.

The Director, Data Strategy & Activation Readiness leads the pillar responsible for that foundation — and for the portfolio of data products built on top of it. This is a builder's role for a leader who can set data strategy, shape a multi-year data product portfolio, stand up governance and identity, and make trusted, activation-ready data self-serve across the marketing organization. You will own the data and platform layer that feeds our analytics partners the clean, connected, closed-loop signal they need to prove and grow marketing's impact — while tying every data product to measurable value.You'lloperatein a highly matrixed environment as the alignment hub across the Enterprise Data Office, Analytics, Technology, Privacy, and Legal.

What You'll Do

SET THE DATA AND DATA-PRODUCT STRATEGY

• Own the end-to-end marketing data strategy— the roadmap that moves the organization from fragmented, list-pull-driven data to a unified, governed, identity-resolved foundation.

• Define andmaintaina multi-year data product portfolio plan— surfacing new opportunities, modernization needs, and rationalization paths as priorities evolve.

• Establish clear standards for evaluating data product investments— expected value, feasibility, and adoption impact — so the team invests where it matters most.

• Champion data democratization— stand up self-serve access so marketers, andover timepartners across Distribution, HR, and beyond, can query trusted data directly without manual pulls or analyst dependency.

BUILD AND SCALE ACTIVATION-READY DATA PRODUCTS

• Define, build, andproductizecertified, AI-ready data productsthat are activation-ready out of the box, with no data preprequired.

• Institutionalize the full data product lifecycle— from discovery and design through build, launch, iteration, and retirement.

• Drive user-centric product design— reliability, clarity, trust, and accessibility built in from the start.

• Define KPIs, success metrics, and ROI models for every data product, ensuring each one measurably improvesdecisioning, operational efficiency, omnichannel performance, and AI readiness.

• Own the marketing data intelligence layer— oversee its implementation and ongoingmanagementso signals from every platform and source are clean, connected, structured, and ready for activation and measurement.

ESTABLISH GOVERNANCE, IDENTITY, AND TRUST

• Establish and run the marketing data governance operating model— data quality SLAs, stewardship, standards, and clear accountability.

• Oversee metadata management, data lineage, and the data catalogso every data asset is discoverable, documented, and trusted.

• Evaluate, select, and implement an identity resolution capabilityto stitch identities across sources into one persistent, trusted customer and advisor profile — the enterprise identity spine.

• Align toenterprise standardsby partnering with the Enterprise Data Office to keep marketing governance and identity consistent with enterprise policies and frameworks.

ENSURE PRIVACY, COMPLIANCE, AND RESPONSIBLE DATA USE

• Ensure all marketing data is captured, stored, and used compliantly— consent-aware and privacy-first — in partnership with Privacy, Legal, and Compliance.

• Proactively manage data and operational riskalongside Legal, Compliance, and Security, embedding privacy-by-design across the foundation and every activation path.

• Championresponsibledata usage and ethical AI practicesacross every data product and decisioning path.

POWER ACTIVATION AND CLOSED-LOOP MEASUREMENT

• Own the data and audience layer of the CDP and marketing automation platforms(e.g., Adobe Experience Platform, Marketo,SFMC) —ensuring profiles, segments, and audiences are governed,accurate, and activation-ready.

• Ensure data is captured from all sources— every channel, event, and touchpoint — and instrumented so the analytics team can execute closed-loop measurement and attribution.

• Own campaign taxonomy, signal/event capture, and attribution data re-ingestionso measurement becomes a continuous growth engine rather than a rear-view report.

MONITOR, MEASURE, AND CONTINUOUSLY IMPROVE

• Implement ongoing performance monitoring across data products— availability, quality, usage, satisfaction, and business outcomes.

• Champion iteration and innovationthrough user feedback, usage insights, and emerging technology — continuously raising the bar on trust and value.

LEAD ACROSS THE MATRIX

• Serve as the alignment hubfor priorities, standards, roadmaps, and delivery timelines across Marketing, Analytics, Technology, Data Engineering, the Enterprise Data Office, Privacy, and Legal.

• Operate effectively without direct authority— influencing and aligning a complex stakeholder landscape.

• Manage up with clarity and confidence— keeping senior leadership informed, aligned, and bought in on strategy, trade-offs, and progress.

• Lead a blended teamof employees and contractors spanning governance& readiness and delivery & automation.

What You Bring

REQUIRED QUALIFICATIONS

• 10+ years of progressive experience in data strategy, data management, data product management, or marketing data and technology, including time ina leadershipor lead-architect capacity.

• Experience building and scaling data products or enterprise data platforms.

• Demonstrated ownership of core data governance disciplines — metadata management, data lineage, data cataloging, data quality, and stewardship.

• Hands-on experience evaluating and implementing identity resolution / identity graph capabilities and CDP platforms.

• Deep working knowledge of the modernMarTechand data stack — CDP (e.g., Adobe Experience Platform), marketing automation (e.g., Marketo, SFMC), and enterprise data environments (EDW / datawarehouse) —plus a solid grasp of modern data engineering and architecture.

• Proven ability to partner with senior business executives, translate their priorities into roadmaps, and drive measurable value.

• Strong command of data privacy and consent requirements, and how to operationalize compliant data management in a regulated environment.

• Experience enabling analytics and measurement teams through instrumentation, taxonomy, and data capture that support closed-loop measurement and attribution.

• Excellent communication, stakeholder management,upward-management, and executive storytelling skills, including close partnership with an Enterprise Data Office or equivalent central data function.

PREFERRED QUALIFICATIONS

• Experience in financial services, insurance, oranotherregulated, data-sensitive industry.

• Familiarity with AI/ML enablement — preparing AI-ready data and supporting model deployment and real-time decisioning.

• Fluency with cloud-native data stacks and modern product management methodologies (Agile, Design Thinking, Lean Product).

• Bachelor's degree in a relevant field (data, computer science, engineering, analytics, or business); an advanced degree is a plus.

• Relevant certifications welcomed — e.g., data governance, Adobe/Salesforce platform credentials, or privacy (such as CIPP/US).

The Ideal Candidate

• A strategist and a builder— comfortable setting vision and rolling up sleeves to stand up capabilities from the ground up.

• A product thinker— treats data as a product, obsessing over adoption, usability, and the value it creates for the people who use it.

• A translator— fluent in both business and marketing outcomes and the technical realities of data, platforms, and governance.

• An influencer— earns trust and drives alignment across senior and cross-functional stakeholders without leaning on authority.

• A steward— brings discipline and accountability to data quality, governance, privacy, and responsible AI.

• Biased for action— moves from strategy to production quickly, favoring standardization and speed.

• Outcome-oriented— ties every data investment tomeasurablemarketing impact.

How Success Is Measured

• Adoption and business impact of data products across marketing and partner functions.

• Demonstrated value creation — operational efficiency, decision velocity, omnichannel performance, and AI enablement.

• Maturity and effectiveness of the data product operating model.

• Quality and satisfaction of cross-functional partnerships.

• Scalability, performance, and trustworthiness of the data product ecosystem.

Work Arrangement

This is a full-time, hybrid role based in Newark, NJ. The successful candidate is expected to work onsite at the Newark office three (3) days per week, with flexibility to work remotely for the balance of the week.