Director, Principal Data Architect

Universal Orlando•Orlando, FL

12d

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 position leads the design of end-to-end data solutions, including data models, integration patterns, and data platform architecture, and partners with business and technology leaders to connect 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, providing clear direction and recommendations that enable trusted, secure, and reusable data capabilities at enterprise scale. The role translates 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. It evaluates data platform capabilities, tools, and patterns; makes build, buy, or reuse recommendations; rationalizes redundant capabilities; and translates stakeholder needs into documented architecture decisions. It authors and evolves architecture and governance standards, chairs the Data Architecture Review Board, reviews internal, partner, and vendor solution designs, and governs exceptions and architectural debt through closure. As enterprise owner of data governance design, the position defines the governance framework and operating model, including data ownership and stewardship, data domains, quality standards and controls, classification, lineage, and retention. It embeds privacy-by-design, regulatory, and data-residency requirements in partnership with Information Security, Privacy, and Legal, and ensures governance designs are implemented and adopted. It also defines architecture that makes enterprise data ready for machine learning, generative AI, and agentic use cases, establishing standards for AI data quality, lineage, observability, and responsible use, and assessing readiness and remediation needs before build commitments. The Director leads, coaches, and develops data architects and partner resources; builds a repeatable architecture practice with standard artifacts, maturity metrics, and a community of practice; and communicates architecture strategy and decisions to executive, technical, and non-technical audiences. The role carries out supervisory responsibilities in accordance with organizational policies and applicable laws, follows established Universal Orlando Environmental, Health & Safety policies and procedures, and performs other duties as assigned. Consistent attendance is required. Travel of approximately 10% may be required, including domestic and international travel, and flexibility to collaborate across global time zones, including early-morning or evening meetings, is required.

Requirements

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.
Proven experience in data architecture, data engineering, and enterprise data platforms, including significant architecture leadership in complex enterprise environments.
Expert command of conceptual, logical, and physical data modeling, including relational and dimensional modeling; 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/Azure data and AI services, ELT and transformation tooling such as dbt, orchestration, cataloging, and data observability; ability to evaluate platforms objectively for capability, cost, performance, and scalability.
Working knowledge of ML 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.
Demonstrated 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 complex technical options into clear recommendations, influence without authority, and resolve conflicts across competing priorities.
Proficiency with SQL, data modeling tools, data catalogs, and architecture diagramming/repository tools.
Ability to perform each essential duty satisfactorily; reasonable accommodation may be made to enable individuals with disabilities to perform essential functions.
Consistent attendance is a job requirement.

Nice To Haves

Master’s degree in a related field.
Experience architecting data foundations for AI/ML and generative AI solutions running in production.
Experience in global, multi-region organizations with data-residency and cross-border data-sharing requirements.
Experience in hospitality, theme parks, travel, entertainment, or retail, or an equivalent combination of education and experience.
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.

Responsibilities

Translate enterprise data and AI strategy into data architecture strategy, guiding principles, and a multi-year target-state design aligned with business priorities.
Treat data as a strategic business asset and ground architecture decisions in measurable guest-experience, revenue, cost, and risk outcomes.
Evaluate and recommend data platform capabilities, tools, and patterns, including cloud data warehouse and lakehouse, streaming, integration, cataloging, and observability; make build, buy, or reuse decisions and rationalize redundant capabilities.
Partner with business and technology stakeholders to translate needs into architectural direction and document architecture decisions.
Author, publish, and evolve data architecture and data governance standards covering modeling, integration and interoperability, metadata and lineage, master and reference data, and security and access patterns.
Chair the Data Architecture Review Board and 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 framework, operating model, ownership and stewardship structures, data domains, data quality standards and controls, classification, lineage, and retention policies.
Embed privacy-by-design, regulatory, and data-residency requirements in partnership with Information Security, Privacy, and Legal.
Define governance-by-design patterns and partner with platform and engineering teams to ensure governance designs are implemented and adopted.
Define architecture for AI-ready enterprise data, including canonical data models, semantic layers, ontologies and knowledge graphs, data contracts, and feature and vector data patterns.
Establish standards for AI data quality, lineage, observability, and responsible use; assess readiness for proposed AI initiatives and define remediation paths before build commitments.
Lead, coach, and develop data architects, team members, and partner resources, setting expectations and quality standards.
Build a consistent, 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.
Carry out supervisory responsibilities in accordance with organizational policies and applicable laws.
Follow established Environmental, Health & Safety policies, procedures, training, and team-member involvement activities.
Maintain consistent attendance; travel approximately 10% as required and collaborate across global time zones, including early-morning or evening meetings.
Perform other duties as assigned.