Director, Principal Data Architect

Universal Orlando•Orlando, FL

13d

About The Position

The Director, Principal Data Architect leads the data architecture pillar for Universal Destinations & Experiences (UDX), shaping the enterprise data foundation to support growth, innovation, and AI transformation. The role translates Enterprise Data & AI vision into an executable strategy and target-state architecture, modernizing platforms and enabling advanced analytics, intelligent automation, and AI-powered solutions. It leads end-to-end data solution design, including data models, integration patterns, and data platform architecture, while connecting 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 chairs the Data Architecture Review Board (DARB). The role defines enterprise governance frameworks, operating models, standards, and controls; embeds privacy, regulatory, and data residency requirements into architecture; and establishes data foundations and readiness patterns for machine learning, generative AI, and agentic use cases. It also builds a consistent architecture practice and communicates strategies and decisions to executive, technical, and non-technical audiences. The position requires a bachelor’s degree in a related field and extensive experience in data and enterprise architecture, governance, cloud-scale data platforms, and technical leadership. A master’s degree and relevant certifications are preferred. Travel of approximately 10% may be required, and flexibility to collaborate across global time zones, including early-morning or evening meetings, is required. The role includes supervisory responsibilities and requires consistent attendance. Reasonable accommodation may be made to enable individuals with disabilities to perform essential functions.

Requirements

Bachelor’s degree in Computer Science, Information Systems, Engineering, Mathematics, or a related field.
12+ years of experience in data, technology, or engineering roles, including 10+ years in data architecture, data engineering, or data platform leadership.
5+ 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.
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+ years leading, coaching, or managing architects or senior technical staff, including directing external partners and vendors.
Expertise in conceptual, logical, and physical data modeling; relational and dimensional models; data product and domain design; lakehouse and cloud data warehouse patterns; batch and 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 including 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 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, make timely and defensible decisions, balance standards with pragmatic delivery, and manage exceptions transparently.
Ability to connect data architecture to business outcomes, articulate and measure the value of data assets, and prioritize architecture investments by business impact.
Executive presence and strong written and verbal communication; ability to distill technical options into recommendations, influence without authority, and resolve conflicts across competing priorities.
Proficiency with SQL, data modeling tools, data catalogs, and architecture diagramming/repository tools.
Consistent attendance is required.
Flexibility to collaborate across global time zones, including early-morning or evening meetings, is required.

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, or an equivalent combination of education and experience.
Relevant certifications, 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 multi-year target-state design aligned with UDX business priorities.
Evaluate and recommend data platform capabilities, tools, patterns, and build/buy/reuse decisions; rationalize redundant capabilities.
Work with business and technology stakeholders to translate needs into architectural direction and documented architecture decisions.
Author, publish, and evolve data architecture and governance standards covering 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, operating model, ownership and stewardship structures, domain definitions, data quality controls, classification, lineage, and retention policies.
Embed privacy-by-design, regulatory, and data residency requirements in architecture in partnership with Information Security, Privacy, and Legal.
Define governance-by-design patterns and partner with platform and engineering teams to implement and adopt them.
Define architecture for AI-ready enterprise data, including canonical models, semantic layers, ontologies, knowledge graphs, data contracts, and feature and vector data patterns.
Establish standards for AI data quality, lineage, observability, and responsible use; assess data readiness for AI initiatives and define remediation paths.
Lead, coach, and develop data architects, team members, and partner resources, setting 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 Universal Orlando policy, procedures, training, and team member involvement activities related to Environmental, Health & Safety responsibilities.
Carry out supervisory responsibilities in accordance with organizational policies and applicable laws.
Travel up to approximately 10% as required and collaborate across global time zones, including early-morning or evening meetings.
Perform other duties as assigned.