Responsibilities

• Architecture & Design: Define and deliver solution architectures for CDP, Customer Master Data, Customer 360, marketing automation, personalization, and attribution ecosystems. Establish target-state architecture across CDP, Data Warehouse, and Customer Master Data with clear separation of concerns between data mastering, activation, and analytics.
• Integration: Ensure seamless connectivity between MarTech platforms, AdTech tools, data platforms, CMS/DAM systems, and analytics ecosystems.
• Identity & Governance: Define and govern identity resolution, enterprise customer ID strategy, and consent enforcement, ensuring compliance with privacy regulations and enterprise data policies.
• Personalization & Decisioning: Architect real-time and batch decisioning frameworks, enabling scalable personalization, experimentation, and ML-driven customer engagement.
• Data & Content Technology Strategy: Define standards for data flows, identity management, customer mastering approaches, and content governance across platforms.
• Retail Media & Activation: Enable first-party data activation across paid media and Retail Media Networks, supporting audience creation, targeting, and monetization.
• Vendor Strategy & Cost Optimization: Evaluate MarTech and AdTech platforms, drive build vs buy decisions, and optimize platform usage and cost, including CDP unit economics.
• Innovation & Strategy: Stay ahead of trends in MarTech, AdTech, AI, and analytics, recommending new technologies and approaches that drive measurable business outcomes.
• Governance & Oversight: Serve as design authority for customer data and marketing technology, ensuring scalability, security, compliance, and alignment with enterprise architecture standards.
• Collaboration: Partner with Marketing, Product, IT, Data Science, and vendors to align on roadmaps, define capability-driven Architecture models, and deliver reusable, scalable solutions.

Requirements

• Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related field (master’s degree a plus).
• 8+ years of experience in customer data, data engineering, or MarTech domains, with at least 3 years in marketing technology architecture, including personalization and customer engagement solutions
• MarTech data domain expert skilled in customer data, clickstream, identity resolution, segmentation, and activation across owned, paid, and partner channels
• Proven expertise in CDP (COTS or in-house), Customer Master Data management, CRM/loyalty systems, and Customer 360 solutions.
• Experience defining identity resolution strategies (first-party, hybrid, and third-party) and understanding tradeoffs across CDP, data warehouse, and external identity providers.
• Experience implementing privacy, consent management, and data governance frameworks, including consent enforcement and data lineage.
• Experience designing architectures for personalization, ML decisioning, loyalty programs, closed-loop measurement, and attribution.
• Hands-on experience with marketing automation platforms (ESP/SMS/Push) integrated with customer data and analytics platforms.
• End-to-end experience across the MarTech and AdTech stack, spanning CDP, Customer Master Data, personalization engines, paid media platforms, analytics, attribution, and customer data activation.
• Background integrating CMS/DAM platforms with personalization and engagement ecosystems.
• Experience supporting Retail Media Networks (RMN), audience monetization, and paid media activation using first-party data.
• Experience evaluating and selecting MarTech /AdTech platforms, including build vs buy decisions and vendor architecture assessments.
• Skilled in high-volume, high-velocity data ingestion architectures (batch and streaming).
• Experience working with Data Science teams to operationalize ML models into customer-facing workflows.
• Exposure to AI-driven engagement, automation, and GenAI is considered a plus.
• Proficiency with MarTech/AdTech platforms such as Salesforce Marketing Cloud, Adobe Experience Cloud, Braze, HubSpot, Google Analytics, or similar ecosystems.
• Customer Data: Customer Data Platforms, Customer Data Warehouse, Customer Master Data, Customer 360
• Identity Resolution: First-party, hybrid, and third-party identity graphs, deterministic and probabilistic matching
• Marketing Platforms: ESP/SMS/Push, CRM, CMS/DAM, personalization, and decisioning engines
• AdTech/Media: Paid media platforms, attribution frameworks, Retail Media Networks, audience activation

Preferred

• Exposure to AI-driven engagement, automation, and GenAI is considered a plus.