Job ID: 2023-17105 Type: Full-Time # of Openings: 1 Category: Information Technology
Princeton University
Overview
The Domain Architect, part of the University Data Office, is a key role providing expertise and support for data across one of several key cross cutting domains (Student, Faculty & Research, People, Finance & Services). The position interacts closely with a broad range of offices and functions to facilitate the maintenance of rich institutional data and its translation into useful information for analysis and insight. The position requires senior analyst experience, project management acumen, and subject matter expertise for data across the domain as well as the standards and conventions required for proper collection, quality, definition, translation, and use.
The University Data Office is a unit established by the Office of the Provost with responsibility for developing and incorporating a campus-wide data strategy to support strategic decision making by serving as the nexus between the strategic questions, the data resources, the technical solutions, and information consumers.
The Domain Architect will serve as a point of organization and support for collaborative work within and across domains. Enabling a robust analytics culture is an essential pillar of the University's data strategy. For the University's strong and capable core of data analysts to focus on deriving insights instead of finding and securing, preparing and massaging data requires supportive resources with expertise across the source applications, stewards and business processes, organizations, reporting life cycles, and compliance requirements of the domain. The position is an important contributor to the institutional information model and data governance, working closely with data stewards and analysts to develop and maintain consistent data definitions and to collate the nuances in meaning, merging, and interpretation; and working with stewards and application managers to assure that appropriate and consistent data collection and quality standards are maintained across the wide array of domain related sources.
Responsibilities
INFORMATION MODEL
Collaborate with stakeholders including data stewards, data scientists and analysts, and IT data teams
Build and maintain a comprehensive inventory of internal and external data sources for the domain.
Identify data assets for the domain including key or common data across sources.
Understand and break down complex cross-domain strategic analytic needs into required data components and fit gap to the existing data inventory.
Rationalize and document business rules and context for codification into the central integrated analytics layer.
Work with the Information Architect to incorporate into the institutional model.
Lead Data Readiness and Strategic Information Assessments, representing the UDO in establishing information needs and reporting strategy prior to RFP/selection/implementation of systems and applications in the domain.
INFORMATION MANAGEMENT
Support working groups of stewards and subject matter experts to document, iterate, contextualize, rationalize/normalize, and formalize master and metadata for the domain including categorizing restricted and confidential data.
Work with Information Architect and IT Metadata and Access specialists to translate the design for master and metadata into the data governance technology platform.
Work with stewards, application managers, and analysts to profile key data, define collection and quality requirements for the data to serve strategic analytic purposes, including 'gap' data.
Synchronize data standards cross all nodes in the domain, from collection to acquisition (for analytics) through retention to promote consistency and quality.
Work across steward, application, and data teams to implement new data collections, maintain a view of quality, apply classification and retention guidelines, etc.
COMMUNICATION AND ENGAGEMENT
Serve as an information expert for a domain that includes many sources and systems, business processes, departments, and stakeholders.
Become highly proficient in understanding how data is used and coded, current and desired standards, business rules and context for translating the data into analytics insight.
Bridge between the many disparate efforts related to the final delivery of analytics involving data in the domain - including data representation, data integrity and accuracy, data access and protection, regulatory compliance, and data dissemination.
Serve as a guide able to navigate the full domain lifecycle to assist analysts, application and data teams, and information consumers.
Serve as Subject Matter Expert to support assessment and project proposals, data requests, projects etc., where domain data expertise is needed.
Cultivate relationships with traditional and emerging data providers and subject matter experts to identify and clarify new and existing data assets that may include external, device, survey, benchmark and types.
Expand awareness of the data and studies available for the domain, knowledge and appropriate use of domain data, communicate use cases, participate in information literacy programs to train analysts and information consumers on sources, data definitions, and limitations.
Qualifications
⢠5+ years recent experience working (in the domain) in a data driven role such as data analytics, subject matter expert re: acquisition/profiling/business rules definition, or governance.
⢠3+ years recent experience working in a lead role in data management initiatives such as data dictionary/definition, data quality, and/or reporting/dashboard development.
⢠3+ years experience as a business analyst or project manager with strong acumen for synthesizing and resolving multiple inputs into a data management structure such a metadata model or security/access model.
⢠Superior analytic and problem solving skills to navigate, document, and address a variety of data nuances, business transformations and complex data logic.
⢠Familiarity with enterprise data models that support cross domain integration and analysis.
⢠Exceptional interpersonal skills, communication (oral and written) skills, and the ability to engage effectively with the diverse experiences and perspectives of data stewards and subject matter experts, application managers, and IT teams.
⢠Excellent planning and organization skills to estimate, track, and complete projects and deliverables
⢠Experience discussing complex and new topics in an easy-to-understand way.
Preferred
⢠Experience and cross-functional knowledge of functional domains of an R1 higher education institution. ⢠Experience as a data analyst working with complex integrated datasets.
Princeton University is an Equal Opportunity/Affirmative Action Employer and all qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity or expression, national origin, disability status, protected veteran status, or any other characteristic protected by law. KNOW YOUR RIGHTS
Princeton University is a vibrant community of scholarship and learning that stands in the nation's service and in the service of all nations. Chartered in 1746, Princeton is the fourth-oldest college in the United States. Princeton is an independent, coeducational, nondenominational institution that provides undergraduate and graduate instruction in the humanities, social sciences, natural sciences and engineering.As a world-renowned research university, Princeton seeks to achieve the highest levels of distinction in the discovery and transmission of knowledge and understanding. At the same time, Princeton is distinctive among research universities in its commitment to undergraduate teaching.Today, more than 1,100 faculty members instruct approximately 5,200 undergraduate students and 2,600 graduate students. The University's generous financial aid program ensures that talented students from all economic backgrounds can afford a Princeton education.