Enterprise Data Architect

The Data Architect provides high-level technical leadership and strategic design for the University's enterprise data ecosystem. This role is responsible for the creation of comprehensive logical and physical data models that serve as the authoritative blueprints for the University's Information Technology Services (ITS) division, mainly for analytical and AI purposes. Operating at the intersection of transactional software development and analytical systems, the Data Architect ensures that all data structures are designed for maximum interoperability, integrity, and scalability. This position is central to the University's transition toward a cloud-native data architecture, with our data warehouse being built cloud-native and a current initiative to move all on-premise applications to the cloud. The role functions as a critical consultant to both Software Development and Data Engineering teams, establishing the standards that govern the lifecycle of data across the institution. A primary objective of this position is to ensure AI-readiness by architecting clean, well-governed, and highly structured datasets that can support advanced machine learning and large language model (LLM) implementations. The Data Architect is expected to proactively integrate into development workflows to provide architectural oversight, ensuring that new applications and enhancements align with the University's long-term data strategy. Our ITS team operates in an "Agent First" mindset. This position will be involved in thought-leadership on how agents can support architecture decisions and ensure standards are met. This position does not focus on hardware or technology procurement but rather on the structural logic and semantic consistency required to maintain a unified institutional "Source of Truth." This position is classified as predominantly remote with occasional visits to campus as needed. Working hours will be based on Pacific Standard Time (PST). The full salary range for the Data Architect is $114,300 - $220,900 annually. However, the pay scale for this position is up to $160,000 annually. We base salary offers on a variety of considerations, such as education, licensure and certifications, experience, and other business and organizational needs. Applicants must have current work authorization when accepting a UCR staff position. Currently, UCR is unable to sponsor or take over sponsorship of an employment Visa for staff. As a University employee, you will be required to comply with all applicable University policies and/or collective bargaining agreements, as may be amended from time to time. Federal, state, or local government directives may impose additional requirements.\n \nInitiates, designs and deploys large scale systems. Designs highly complex user systems interfaces, business software prototypes and new systems or major enhancements to existing programs.Translates high-level business requirements from stakeholders and data stewards into granular technical data specifications. Analyzes the feasibility of integrating new data streams into the existing ecosystem and evaluates how changes in transactional source systems will impact downstream analytical models and institutional metrics.Applies advanced IT architecture concepts to function as the highest level technical expert. Often serves as consultant to management. May lead or provide guidance to large development team in design of highly complex software systems. Advises on selection of technological purchases with regards to processing, data storage, data access and software development.Defines the source of truth for institutional datasets (e.g., Student, Faculty, Course). Establishes the structural standards that ensure data is secure by design. Ensures that the Semantic Layer is architected so that disparate departments can consume data through a unified, governed lens. Together with data stewards, ensure the data dictionary is complete and up-to-date for all institutional datasets.Partners with Data Engineering, Infrastructure, and Database Administration teams to ensure that architectural designs are successfully deployed and performant. Acts as the bridge between the "Blueprint" (Design) and the "Build" (Implementation), ensuring the final technical environment accurately reflects the intended data models and security protocols.\n \nKnowledge of software, database, infrastructure or other IT function. Knowledge relating to the design and development of software across the organization.Knowledge of other related areas of IT. Ability to apply department processes and procedures to work.Demonstrated effective communication and interpersonal skills, including the ability to communicate technical information to technical and non-technical personnel at various levels in the organization.Ability to understand business needs and how business systems can support those needs.Demonstrated ability to work with others from diverse backgrounds.Self-motivated and works independently and as part of a team. Demonstrates problem solving skills. Able to learn effectively and meet deadlines.Demonstrated ability to translate business needs into long-term architecture solutions. Expertise relating to the design and development of software across the organization.Advanced knowledge of data storage, processing, and analysis and how they are used in administrative, medical and/or academic endeavors.Understanding of and experience with key modeling and description languages used to map complex business processes to architectural components, develop common data resource architectures, and create reference frameworks.Experience with the integration of complex, diverse, internally and externally developed implementations of business functions to build scalable systems.Mastery of both Relational Modeling (3rd Normal Form) for transactional systems and Dimensional Modeling (Star/Snowflake schemas) and denormalized for data warehousing.Ability to create high-level Entity Relationship Diagrams (ERDs) and data flow diagrams that serve as the authoritative blueprint for development teams. Ability to explain complex architectural concepts to both "downstream" Data Engineers and "upstream" Software Developers.Knowledge of Master Data Management (MDM) and the ability to define and maintain a centralized data dictionary/business glossary.Proven ability to establish, document, and evangelize enterprise data standards that cross-functional teams (Software Dev and Data Engineering) are motivated to follow.May require skills in web software, web software language and object oriented software concepts. May require knowledge of network protocols and how they are used on a large (campus/medical center/OP-wide, institution-wide or beyond) network. May require advanced knowledge of data storage, processing analysis and visualization technologies and how they are used in administrative and/or academic endeavors at a large, top-tier research university or medical center.Advanced ability to translate vague business requests from University stakeholders into granular technical specifications and data requirements. Familiarity with common University data domains (e.g., Student Information Systems (SIS), Financials, CRM, and Research Administration).Expert-level SQL skills to query complex datasets, validate models, and perform deep-dive data profiling across disparate systems.Ability to serve as a "Lead by Example" figure, providing clear, actionable blueprints and documentation that reduce friction for implementation teams rather than creating bureaucratic hurdles. Advanced interpersonal skills with the ability to navigate complex institutional silos. Must be able to "sell" the long-term value of structured architecture to stakeholders who may be focused on short-term delivery speed.Experience with automated data cataloging or lineage tools (e.g., Collibra, Alation, or open-source equivalents).Knowledge of the use of AI agents in day-to-day work and how to support other teams through agents to guide their architecture work.\n \nKnowledge of software, database, infrastructure or other IT function. Knowledge relating to the design and development of software across the organization. Ability to understand business needs and how business systems can support those needs. Demonstrated ability to work with others from diverse backgrounds. Experience with the integration of complex, diverse, internally and externally developed implementations of business functions to build scalable systems. Demonstrated effective communication and interpersonal skills, including the ability to communicate technical information to technical and non-technical personnel at various levels in the organization. Self-motivated and works independently and as part of a team. Demonstrates problem solving skills. Able to learn effectively and meet deadlines. Demonstrated ability to translate business needs into long-term architecture solutions. Expertise relating to the design and development of software across the organization. Advanced knowledge of data storage, processing, and analysis and how they are used in administrative, medical and/or academic endeavors. Understanding of and experience with key modeling and description languages used to map complex business processes to architectural components, develop common data resource architectures, and create reference frameworks. Knowledge of other related areas of IT. Ability to apply department processes and procedures to work. Proven ability to establish, document, and evangelize enterprise data standards that cross-functional teams (Software Dev and Data Engineering) are motivated to follow. Mastery of both Relational Modeling (3rd Normal Form) for transactional systems and Dimensional Modeling (Star/Snowflake schemas) and denormalized for data warehousing. Ability to create high-level Entity Relationship Diagrams (ERDs) and data flow diagrams that serve as the authoritative blueprint for development teams. Ability to explain complex architectural concepts to both "downstream" Data Engineers and "upstream" Software Developers. Knowledge of Master Data Management (MDM) and the ability to define and maintain a centralized data dictionary/business glossary.May require skills in web software, web software language and object oriented software concepts. May require knowledge of network protocols and how they are used on a large (campus/medical center/OP-wide, institution-wide or beyond) network. May require advanced knowledge of data storage, processing analysis and visualization technologies and how they are used in administrative and/or academic endeavors at a large, top-tier research university or medical center. Advanced ability to translate vague business requests from University stakeholders into granular technical specifications and data requirements. Familiarity with common University data domains (e.g., Student Information Systems (SIS), Financials, CRM, and Research Administration). Knowledge of the use of AI agents in day-to-day work and how to support other teams through agents to guide their architecture work. Expert-level SQL skills to query complex datasets, validate models, and perform deep-dive data profiling across disparate systems. Ability to serve as a "Lead by Example" figure, providing clear, actionable blueprints and documentation that reduce friction for implementation teams rather than creating bureaucratic hurdles. Advanced interpersonal skills with the ability to navigate complex institutional silos. Must be able to "sell" the long-term value of structured architecture to stakeholders who may be focused on short-term delivery speed. Experience with automated data cataloging or lineage tools (e.g., Collibra, Alation, or open-source equivalents).