Director, Principal Data Architect

Universal Orlando•Orlando, FL

About The Position

The Director, Principal Data Architect shapes the data foundation for Universal Destinations & Experiences’ growth, innovation, and AI transformation. Leading the data architecture pillar, this role translates the Enterprise Data & AI vision into an executable strategy and target-state architecture that modernizes platforms and enables advanced analytics, intelligent automation, and AI-powered solutions. The role leads the design of end-to-end data solutions, including data models, integration patterns, and data platform architecture. In partnership with business and technology leaders, the Director connects architecture decisions to measurable improvements in guest experience, revenue, and operations. This hands-on leader develops the data architecture team, owns data governance design and architecture standards, and leads the Data Architecture Review Board to provide direction and recommendations that enable trusted, secure, and reusable data capabilities at enterprise scale.

Requirements

Proven experience in data architecture, data engineering, and enterprise data platforms, including significant leadership of architecture in complex enterprise environments.
Expert command of conceptual, logical, and physical data modeling, including relational and dimensional models; data product and domain design; lakehouse and cloud data warehouse patterns; batch and real-time/streaming integration; APIs; and event-driven architecture.
Deep expertise designing enterprise data governance frameworks and operating models, including ownership and stewardship, data domains, data quality controls, classification, metadata, lineage, and master data management, aligned to DAMA-DMBOK or equivalent.
Working knowledge of privacy, security, and regulatory requirements such as GDPR/UK GDPR, CCPA/CPRA, Japan APPI, and PCI DSS, including cross-border data residency and sharing.
Deep knowledge of Snowflake and AWS and/or Azure data and AI services, ELT and transformation tooling such as dbt, orchestration, cataloging, and data observability; ability to evaluate platforms for capability, cost, performance, and scalability.
Working knowledge of machine learning platforms and MLOps, feature stores, vector databases, retrieval-augmented generation, semantic layers, ontologies/knowledge graphs, and AI data governance patterns.
Ability to lead architecture review forums and make timely, defensible decisions, balancing standards with pragmatic delivery and managing exceptions transparently.
Ability to connect data architecture to business outcomes, articulate and measure the value of data assets, and prioritize architecture investments based on business impact.
Executive presence and exceptional written and verbal communication; ability to distill technical options into clear recommendations, influence without authority, and resolve conflict across competing priorities.
Proficiency with SQL, data modeling tools, data catalogs, and architecture diagramming/repository tools.
Bachelor’s degree in Computer Science, Information Systems, Engineering, Mathematics, or a related field.
12 or more years of experience in data, technology, or engineering roles, including 10 or more years in data architecture, data engineering, or data platform leadership.
5 or more years in an enterprise, principal, or lead data architect role setting architecture strategy and standards across multiple domains and platforms.
Experience designing and implementing an enterprise data governance framework and operating model in a large, complex organization.
Demonstrated experience chairing an architecture review board or equivalent governance forum and issuing binding architectural decisions.
Experience designing and delivering cloud-scale data platforms using Snowflake, AWS, and/or Azure, including platform evaluation and selection.
3 or more years leading, coaching, or managing architects or senior technical staff, including directing external partners and vendors.
Consistent attendance is a job requirement.
Reasonable accommodation may be made to enable individuals with disabilities to perform the essential functions.

Nice To Haves

Master’s degree in a related field.
Experience architecting data foundations for production AI/ML and generative AI solutions.
Experience in global, multi-region organizations with data residency and cross-border data-sharing requirements.
Experience in hospitality, theme parks, travel, entertainment, or retail.
Relevant certifications preferred, such as TOGAF, DAMA Certified Data Management Professional (CDMP), SnowPro Advanced: Architect, AWS Certified Solutions Architect – Professional, or Microsoft Certified: Azure Solutions Architect Expert.
Equivalent combination of education and experience.

Responsibilities

Translate enterprise data and AI strategy into data architecture strategy, guiding principles, and multi-year target-state design aligned with business priorities across guest, commercial, and operational domains.
Evaluate and recommend data platform capabilities, tools, and patterns, including cloud data warehouse and lakehouse, streaming, integration, cataloging, and observability; make build, buy, and reuse recommendations and rationalize redundant capabilities.
Work with business and technology stakeholders to turn needs into documented architectural direction and decisions.
Author, publish, and continuously evolve data architecture and data governance standards for modeling, integration, interoperability, metadata, lineage, master and reference data, security, and access.
Chair the Data Architecture Review Board; own its charter, entry criteria, review cadence, decision rights, and escalation paths.
Review solution designs from internal teams, delivery partners, and vendors; issue approval, conditional approval, or rejection recommendations; and govern exceptions and architectural debt through closure.
Own enterprise data governance design, including the governance framework and operating model, data ownership and stewardship, domain definitions, data quality standards and controls, classification, lineage, and retention policies.
Embed privacy-by-design, regulatory, and data residency requirements into architecture in partnership with Information Security, Privacy, and Legal.
Define governance-by-design patterns and work with platform and engineering teams to implement and adopt them.
Define architecture that makes enterprise data ready for AI, including canonical data models, semantic layers, ontologies and knowledge graphs, data contracts, and feature and vector data patterns for machine learning, generative AI, and agentic use cases.
Establish standards for AI data quality, lineage, observability, and responsible use; assess data readiness for proposed AI initiatives and define remediation paths before build commitments.
Lead, coach, and develop data architects, team members, and partner resources; set expectations and quality standards.
Build a repeatable data architecture practice with standard artifacts, maturity metrics, and a community of practice.
Communicate architecture strategy and decisions to executive, technical, and non-technical audiences.
Follow established UO Environmental, Health & Safety policies, procedures, training, and team member involvement activities.
Perform other duties as assigned.
Carry out supervisory responsibilities in accordance with organizational policies and applicable laws.
Travel up to approximately 10% may be required, including domestic and international travel to UDX destinations and partners.
Collaborate across global time zones, including early-morning or evening meetings with international teams.