What are the responsibilities and job description for the Solution Architect, Customer Data position at KnowIt Training?
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.
- 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.