Bachelor's in Computer Science or related field; Master's preferred
8+ years in customer data or MarTech, 3+ in marketing technology architecture
Expertise in customer data, identity resolution, and cross-channel activation
Proven experience with CDP, Customer Master Data, and Customer 360 solutions
Skilled in implementing data governance and consent management frameworks
Background in integrating CMS/DAM platforms and personalization engines
Hands-on experience with marketing automation and customer analytics platforms
Responsibilities
Define solution architectures for Customer Data Platform (CDP) and marketing ecosystems
Ensure connectivity between MarTech, AdTech, and analytics platforms
Manage identity resolution and compliance with privacy regulations
Architect frameworks for real-time personalization and machine learning engagement
Establish standards for data flows and content governance
Activate first-party data for paid media and audience monetization
Evaluate MarTech platforms and drive cost optimization strategies
Stay tuned to trends in MarTech and recommend innovative solutions
Guide design for customer data technology to ensure scalability and security
Collaborate across teams to deliver scalable solutions and align on roadmaps
Benefits
Comprehensive health benefits
Generous paid time off policy
Professional development and training opportunities
Flexible working hours and remote work options
Inclusive and diverse work environment
Full Job Description
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.
Qualification:
Bachelor's degree in Computer Science, Information Systems, Engineering, Or a realted 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
Data Platforms: Data lakes, data warehouses, Lakehouse patterns, structured and unstructured databases
Customer Data Governance: Consent management, data lineage, auditability, data contracts
Architecture Strategy: Build vs buy evaluation, platform scalability, cost optimization, real-time vs batch tradeoffs
AI/GenAI adoption: Leveraging AI/GenAI across marketing use cases and software development to drive personalization, automation, and engineering efficiency.
Process Automation: DevOps, AIOps & automation frameworks for Martech
Excellent communication and presentation skills with the ability to simplify complex concepts for business and executive stakeholders.
Strong problem-solving, creativity, and ability to balance technical rigor with business value.
