Solution Architect, Customer Data
On-siteHouston, Texas, United States
Job Summary
Define and deliver solution architectures for CDP, customer master data, and marketing automation ecosystems. Ensure seamless connectivity between MarTech, AdTech, and analytics platforms while governing identity resolution and consent enforcement. Architect real-time and batch decisioning frameworks to enable scalable personalization and ML-driven engagement. Evaluate MarTech and AdTech platforms to drive build vs buy decisions and optimize unit economics. Partner with Marketing, Product, and Data Science teams to align roadmaps and deliver reusable, scalable solutions. Serve as design authority for customer data and marketing technology, ensuring scalability, security, and alignment with enterprise standards.
Required Qualifications
- Bachelor's degree in Computer Science, Information Systems, Engineering, Or a realted field
- 8+ years of experience in customer data, data engineering, or MarTech domains
- at least 3 years in marketing technology architecture
- experience 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
- Customer 360 solutions
- Experience defining identity resolution strategies (first-party, hybrid, and third-party)
- 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
- Proficiency with MarTech/AdTech platforms such as Salesforce Marketing Cloud, Adobe Experience Cloud, Braze, HubSpot, Google Analytics, or similar ecosystems
- Customer Data Platforms
- Customer Data Warehouse
- Customer Master Data
- Customer 360
- First-party, hybrid, and third-party identity graphs
- deterministic and probabilistic matching
- ESP/SMS/Push
- CRM
- CMS/DAM
- personalization
- and decisioning engines
- Paid media platforms
- attribution frameworks
- Retail Media Networks
- audience activation
- GCP
- AWS/Azure acceptable
- APIs
- microservices
- event-driven architectures (Kafka, Pub/Sub)
- Data lakes
- data warehouses
- Lakehouse patterns
- structured and unstructured databases
- Consent management
- data lineage
- auditability
- data contracts
- Build vs buy evaluation
- platform scalability
- cost optimization
- real-time vs batch tradeoffs
- Leveraging AI/GenAI across marketing use cases and software development
- to drive personalization, automation, and engineering efficiency
- 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
Desired Qualifications
- Master's degree
- Exposure to AI-driven engagement, automation, and GenAI
- considered a plus
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