Director, Enterprise Data Architecture & Readiness

Phillips Edison & Company, Inc.•Cincinnati, OH

About The Position

The Director, Enterprise Data Architecture & Readiness will lead the enterprise data foundation that supports trusted analytics, responsible AI, automation, and faster business decision-making. This role will set the strategy, standards, and operating model needed to make company data more connected, governed, accessible, and decision ready.

Requirements

10+ years of progressive experience in data architecture, enterprise data management, governance, analytics, or related disciplines.
Demonstrated success defining data architecture roadmaps, standards, operating models, and governance practices.
Experience with modern data platforms, cloud or hybrid architectures, integration, master data, metadata, lineage, and data quality.
Enterprise leadership mindset with the ability to move from strategy to execution.
Ability to influence senior leaders across business, technology, legal, compliance, and risk.
Strong communication skills, executive presence, and comfort operating through ambiguity.

Nice To Haves

Experience enabling AI, automation, advanced analytics, or decision intelligence capabilities preferred.

Responsibilities

Define and maintain enterprise data architecture standards, patterns, and reference models.
Guide data model, master data, metadata, lineage, integration, and platform decisions.
Ensure architecture supports analytics, AI, automation, security, and scalability.
Build a practical data readiness roadmap tied to business priorities and decision needs.
Clarify data ownership, definitions, quality expectations, and stewardship routines.
Establish repeatable readiness measures for accuracy, completeness, timeliness, lineage, access, and control.
Use metrics and issue trends to communicate progress, risks, and decisions to senior leaders.
Partner with Legal, Compliance, Security, IT, and business leaders to ensure data practices are secure, compliant, and auditable.
Embed privacy, access, retention, classification, and control requirements into data design.
Promote responsible data and AI practices that are transparent, controlled, and fit for purpose.
Serve as the senior data partner to business, IT, analytics, legal, compliance, security, and risk leaders.
Establish roles, decision rights, governance forums, intake processes, and prioritization practices.
Translate technical complexity into clear business choices and executive-ready recommendations.
Lead change efforts that build data literacy, accountability, and adoption across the organization.