Senior Director Information Architecture - Princeton, United States - Princeton University

Description

Overview

The Senior Director of Information Architecture, reporting to the University Data Officer, leads the design and development of the University's information model that identifies, defines, connects, and contextualizes key data across domains to meet operational, planning, and strategic analytic needs. The position works closely with a broad range of Princeton University's leaders, administrative offices, and IT partners, and requires a balance of strategic acumen, deep experience operationalizing data management, and design expertise to align data collected for operational purposes with data required to achieve strategic goals.

The University Data Office is a unit within the Office of the Provost with responsibility for developing and incorporating a campus-wide data strategy to enable strategic decision making by serving as the nexus between the strategic questions, the data resources, the technical solutions, and the consumers of information.

The institutional information model is an essential pillar of the University's data strategy. To more quickly, easily, flexibly, and consistently harvest insights from data to support operations and strategic planning requires a cohesive, living, top down, transparent, integrated view of the data assets that Princeton needs to collect, maintain, use, and protect.

The Senior Director of Information Architecture will interact with University leaders and stakeholders to understand, synthesize, and translate compelling strategic questions into their data components, relationships, and rules. The position will build a team of functionally facing information and domain architects who will serve as information experts collaborating closely in and across data source and organizational boundaries with data stewards and subject matter experts, analysts and data scientists, and data teams to collect and document the institution's data and integrated analytic needs, business rules, functional nuances and context. The position will work with IT data engineering teams to translate and incorporate the model into central integrated analytics to be used for analysis, generation of insights, planning and projection.

Responsibilities

Leadership

• Lead the design and incorporation of the University's data model, leveraging expertise in information modeling and data management best practices, driven by strategic and functional needs, enabled by technology, and in service of delivering strategic analytics. Collaborate with campus stakeholders to:
  • Understand the institutional drivers and questions requiring strategic analysis.
  • Communicate the objectives and design of the information model to a variety of audiences in functional terms.
  • Establish and promulgate a standards-based approach and design for the information model, master and metadata, incorporation of business rules and context, and other data enrichment approaches.
  • Lead the design, validation, update, and maintenance of the institution's conceptual and logical information models to represent, formalize, and unite the required information to address strategic questions.
  • Anticipate core data needs to collect and organize the data in a disciplined, consistent manner across time, peer groups, and subject matter so that the data will be available and valid to support future as-yet undetermined questions and studies.
  • Create proofs of concepts as necessary for architectural vision and evaluation
• Working as part of the leadership team for the University Data Office:
  • Engage campus partners to plan and incorporate a phased, iterative approach that implements the information model through the delivery of strategic analytic use cases.
  • Develop an institutional approach to master and metadata including the process for documenting definitions and context with campus partners, a standards-based design for the information governance catalog/tool including how to categorize and tag data assets, a structured and streamlined process for entering and maintaining master data and metadata and other data management functions.
  • Engage working groups of data stewards and subject matter experts to document, iterate, contextualize, rationalize/normalize, and formalize master and metadata including aligning on the data lifecycle for key processes and affiliations, and flagging restricted and confidential data.
• Provide advisory services and expertise to unit, OIT, and project teams to ensure that data collection, maintenance, and solutions align with the information architecture and support institutional strategy.
• Actively engage in relevant peer and user communities.

Management

• Provide direction and mentor the team, including feedback, evaluation, and professional development.
• Foster and maintain an environment that is supportive, encouraging, and highly collaborative across the University Data Office.
• Manage stakeholder, consulting, and vendor relationships.
• Model the values and goals of the Office of the Provost.
• Manage and maintain reference architecture (Conceptual and Logical models), including guidelines for designing and developing target state analytic and data management capabilities.
• Manage Domain Architects in working 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.
• Manage Domain Architects in working with stewards, data scientists, and analysts to rationalize and document business rules and context for codification into the curated levels of the integrated analytics layer.
• Guide Domain Architects and IT specialists to translate the metadata/master data design into data catalog platform.
• Guide data engineers responsible for translating and incorporating the information model into the University's integrated data layer for reporting, analytics, and exploration.
• When provided access to restricted or confidential data, manage and protect such data according to the University's standards for security, privacy, and responsible use.

Qualifications

• 15+ years of combined experience in data engineering or software development, business intelligence and reporting, analytics and data science, culminating in data architecture leadership roles.
• 10+ years of leadership experience in data and analytics including at least five years leading the implementation of information architecture programs to represent the data assets of an enterprise.
• 7+ years staff management experience including a demonstrated ability to effectively lead and mentor diverse teams
• 7+ years experience as an information architect developing and managing information architecture models that represent the complex, cross-functional strategic analysis needs of an organization.
• 5+ years experience in information management developing and leading metadata management initiatives.
• Strong knowledge of contemporary approaches for information modeling, MDM, metadata management and their translation to modern technology ecosystems such as data lake, big data systems, data fabric, data mesh, and data warehouses.
• Exceptional interpersonal skills, communication skills (oral and written), and a demonstrated ability to work effectively with and across the diverse experiences and perspectives of institutional leaders, data stewards, IT teams, data scientists and analysts, and information consumers
• Excellent planning and organization skills to estimate, track, and complete initiatives
• Demonstrated ability to navigate between leadership, management, initiatives, and support.
• Demonstrated experience to engage, operate and communicate with project teams at the execution level, as well as with senior leadership at the strategic level.
• Acumen for discussing complex and new topics in an approachable and easy-to-understand way.
• Education: A Bachelor's Degree in computer science, technology, engineering or related field is required. A Masters or advanced degree preferred.

Preferred:

• Experience and cross-functional knowledge of functional domains of an R1 higher education institution.
• Experience building cross-functional enterprise reporting systems and overseeing ongoing maintenance of data.
• 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

Standard Weekly Hours

Eligible for Overtime

Benefits Eligible

Probationary Period

Essential Services Personnel (see policy for detail)

Physical Capacity Exam Required

Valid Driver's License Required

Experience Level