Solution Architect, Customer Data

Knowit Training
Houston, TX, United States
1 day ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
3 years minimum
Working hours
Regular working hours

Tech stack

Adobe Marketing Cloud Application Programming Interfaces (APIs) Artificial Intelligence Amazon Web Services Business Analytics Applications Data Analysis Audit Trail Microsoft Azure Clickstream Information Systems Databases Customer Data Management
+25 more
Information Engineering Data Governance Data Warehousing DevOps Digital Asset Management Enterprise Content Management Google Analytics Identity and Access Management Systems Analysis Machine Learning Automation of Marketing Software Engineering Data Streaming Google Cloud Data Ingestion Event Driven Architecture Data Lakes Information Technology Data Lineage Apache Kafka Data Management Hubspot AIOps User Identification Microservices

Job description

  • 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

Customer/Client Research, Ecosystems, Marketing Automation Software, Data Warehousing, Content Management Systems (CMS), Digital Asset Management Software (DAM), Adtech, Systems Analysis, Privacy Regulations, Regulatory Compliance, * 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
  • Cloud Platforms: GCP preferred (AWS/Azure acceptable)
  • Integration Patterns: APIs, microservices, event-driven architectures (Kafka, Pub/Sub)
  • 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.

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