Senior Enterprise Data Architect

Enterprise Data Architect

You have opportunities to speak up, solve problems, lead others, and be an owner every day as a senior architectural leader who standardizes how data is defined, mastered, integrated, and consumed—eliminating fragmentation and enabling a consistent enterprise-wide data foundation. You partner closely with business, product, engineering, and analytics teams to align data architecture with strategic priorities while reducing complexity and cost.

At Miller Knoll, the Enterprise Data Architect is accountable for defining and governing the enterprise data strategy and architecture, directly enabling business growth, operational efficiency, and digital transformation. This role establishes a cohesive, scalable data ecosystem that ensures data is trusted, accessible, and actionable across all business domains.

• Define and evolve the enterprise data strategy aligned to business objectives and digital initiatives.
• Establish reference architectures and target-state data patterns supporting operational and analytical use cases.
• Ensure data architecture supports scalability, flexibility, and cost efficiency across cloud and legacy environments.

• Own the definition and governance of the Enterprise Canonical Data Model (CDM) and Global Data Dictionary.
• Standardize core business entities (e.g., Customer, Product, Asset) across all systems and domains.
• Drive adoption of a unified data language to eliminate semantic inconsistencies across teams.

• Define authoritative systems of record for all critical data domains.
• Architect and govern Master Data Management (MDM) strategies, including Golden Record creation and stewardship models.
• Reduce redundancy and conflicting data definitions across platforms.

• Establish and enforce standardized integration patterns (API-first, event-driven, and data streaming).
• Reduce point-to-point integrations and integration debt across the enterprise.
• Govern enterprise data flows to ensure consistency, traceability, and scalability.
• Drive alignment toward modern distributed data architectures (e.g., Data Mesh principles where appropriate).

• Define standards for balancing real-time operational needs with analytical processing requirements.
• Ensure data platforms are optimized for both transaction processing and advanced analytics without excessive cost.
• Guide architecture decisions for high-performance systems and enterprise analytics platforms.

• Establish and enforce enterprise data standards, policies, and governance frameworks.
• Actively participate in domain data governance boards to ensure accountability and adoption.
• Improve data quality, lineage, and transparency across the enterprise.

• Translate complex business requirements into scalable, high-impact data solutions.
• Partner with executive leadership to support strategic decision-making through data.
• Ensure data architecture investments deliver measurable business value.

• Serve as a key member of the Architecture Review Board (ARB), governing adherence to enterprise data standards.
• Lead data architecture reviews across all major initiatives and product domains.
• Drive enterprise-wide reduction of data and technology redundancy (“integration and data debt”).
• Partner with Information Security to align data architecture with security, privacy, and compliance requirements.
• Contribute to enterprise-wide architectural direction, ensuring data is a first-class concern in all solutions.

• Promote a federated, domain-oriented data ownership model with strong central governance.
• Enable hypothesis-driven data engineering, encouraging experimentation and iterative delivery.
• Foster cross-functional collaboration between business, product, engineering, and analytics teams.
• Apply a customer and business outcome lens to all data architecture decisions.
• Continuously evaluate and adopt modern data technologies and practices where they…