Senior Lead Marketing Data Platform Architect

The Role

The Senior Lead Marketing Data Platform Architect is responsible for defining, governing, and evolving Lumen's marketing data platform architecture. This role provides technical leadership for the design and implementation of scalable data products, modern analytics capabilities, AI-ready data structures, and agentic operational frameworks that support the organization's marketing strategy.

As the lead architect for the marketing data ecosystem, this individual will establish the long-term platform vision, define architectural standards, and guide modernization initiatives that enable advanced analytics, personalization, audience activation, measurement, and AI-driven decision-making. The role requires close partnership with engineering, analytics, Adobe, Salesforce, and business stakeholders to ensure the platform remains scalable, governed, secure, and aligned with evolving business needs.

This position is ideal for a forward-thinking architect who is passionate about building AI-native data platforms, enabling intelligent automation, and creating modern data foundations capable of supporting both current and future marketing use cases.

The Main Responsibilities

• Own the architectural vision, governance, performance, and long-term evolution of Lumen's marketing data platform.
• Lead the design, implementation, and operational strategy of Databricks as the strategic platform for marketing data and intelligence.
• Define and maintain scalable data architectures that support analytics, reporting, customer intelligence, personalization, activation, and AI-driven use cases.
• Establish platform standards for data modeling, ingestion, orchestration, observability, testing, security, and environment promotion.
• Design and govern reusable data products that enable trusted, consistent access to marketing data across the organization.
• Drive modernization initiatives that improve platform scalability, simplify architecture, reduce technical debt, and accelerate delivery.
• Define governance standards for metadata management, lineage, schema control, data quality, and lifecycle management.
• Design for AI-native and agentic operations, including automated quality controls, monitoring, validation, testing, deployment, and operational intelligence.
• Partner with Adobe, Salesforce, analytics, engineering, and business teams to ensure seamless integration across the marketing technology ecosystem.
• Evaluate emerging technologies and architectural patterns that improve platform performance, automation, and business value.
• Provide technical leadership and architectural guidance to engineers, analysts, and cross-functional stakeholders.
• Lead architecture reviews, establish design standards, and document technical decisions that support long-term platform sustainability.

What We Look For in a Candidate

• Required Qualifications
  • 8+ years of experience in data engineering, platform architecture, data solutions architecture, or related disciplines.
  • Deep hands-on expertise with Databricks, including Delta Lake, Spark, data engineering, governance, orchestration, and platform architecture.
  • Strong experience designing and implementing modern lakehouse architectures and enterprise-scale data platforms.
  • Advanced data modeling, SQL, and data architecture expertise.
  • Experience designing AI-driven or AI-native data solutions and implementing automation, testing, quality controls, and deployment practices.
  • Strong understanding of metadata management, lineage, observability, data governance, and platform operations.
  • Advanced understanding of Adobe's digital ecosystem, including Web SDK, Launch/Tags, Customer Journey Analytics, and Adobe Experience Platform.
  • Advanced understanding of Salesforce architecture, standard and custom object models, and customer data ecosystems.
  • Demonstrated success translating business requirements into scalable, secure, governed technology solutions.
  • Excellent communication and stakeholder management skills with the ability to influence technical and business audiences

• Preferred Qualifications
  • Experience modernizing or transforming enterprise data platforms.
  • Experience designing agentic or AI-assisted operational frameworks.
  • Experience with MCP, Copilot, or similar AI orchestration technologies.
  • Experience implementing machine learning or generative AI capabilities within enterprise data environments.
  • Experience with DataOps, DevOps, infrastructure-as-code, CI/CD, and automated testing frameworks.
  • Familiarity with marketing platforms including Marketo, Demandbase, ZoomInfo, Dun & Bradstreet, and Quantum Metric.
  • Experience supporting customer data platforms, data warehousing, and advanced marketing analytics environments.
  • Azure platform expertise, including Key Vault, Azure Monitor, networking, and cloud governance.
  • Relevant Databricks, Microsoft Azure, Adobe, or Salesforce certifications.

Compensation