BI Data Architect

Syracuse University•Syracuse, NY

33d

About The Position

The Office of Institutional Data and Reporting (IDR) seeks a Data Architect to lead the transformation of institutional analytics capabilities through innovative data solutions and reporting systems. The successful candidate will architect and optimize advanced analytics environments and data models that serve as the foundation for evidence-informed decision making across the University. This strategic role will integrate current and emerging analytics platforms, business intelligence tools, and artificial intelligence technologies to establish Syracuse University as a leader in higher ed data innovation. The position requires the ability to transition seamlessly between platforms as Syracuse University adopts new systems. The ideal candidate will demonstrate platform-agnostic expertise, focusing on underlying data principles and analytics methodologies that transcend specific tools. This role requires collaborative partnership with the campus data warehouse team to evolve IDR's analytical infrastructure, ensuring seamless integration between traditional data systems and next-generation environments while developing cutting-edge solutions that anticipate & meet the evolving institutional intelligence needs.

Requirements

Bachelor's degree required, strongly preferred in information science, data analytics, data science, computer science, or a related field.
Equivalent combination of education and experience will be considered.
Evidence of ability to work with technical staff and end users to clearly assess needs, develop solutions, and articulate technical requirements is required.
Platform-agnostic mindset with proven ability to transition between different analytics and visualization tools.
Experience with dimensionally modeled data and various database systems (Oracle, SQL Server, cloud-based solutions) strongly desired.
Working knowledge of SQL and data querying languages is strongly desired.
Understanding of data governance, security, and access management principles that apply across multiple platforms.
Current knowledge and experience with AI tools are desired, as is a commitment to maintaining expertise in emerging technologies.
Ability to evaluate and recommend new technologies based on institutional needs rather than platform familiarity.

Nice To Haves

Advanced degree (Master's) is desirable but not required.
Two or more years of work experience in Tableau development and administration is strongly desired.

Responsibilities

Strategic Analytics Platform Management & Adaptation:
Architect and optimize IDR's current analytics environment (Tableau) while preparing for integrating emerging platforms such as Microsoft Fabric, Power BI, or future technologies.
Design flexible, platform-independent data governance structures and access protocols that can be adapted as systems evolve.
Develop migration strategies and change management plans to ensure smooth transitions between analytics platforms.
Inform campus-wide initiatives to establish enterprise analytics standards that transcend specific tools, focusing on sustainable practices that will remain relevant regardless of the underlying technology.
Partner with university offices to create unified data visualization and reporting standards that enhance decision-making consistency while maintaining flexibility to adopt new tools as they emerge.
Advanced Analytics Development & Innovation:
Design and build sophisticated data models and interactive analytics solutions using current and emerging platforms, transforming complex institutional datasets into compelling visual narratives for strategic decision-making.
Maintain expertise in multiple analytics platforms to ensure continuity during technology transitions.
Serve as technical mentor and innovation catalyst for IDR team members, developing their platform-agnostic analytical capabilities while fostering a culture of continuous learning and adaptation.
Pioneer creative solutions for complex analytical challenges by integrating various data sources, AI-enhanced calculations, and predictive modeling capabilities across different technology stacks, establishing methodologies that can be implemented regardless of the specific tools in use.
Emerging Technology Integration & Automation:
Research, evaluate, and integrate new analytics technologies and University approved AI platforms into institutional reporting workflows, transforming manual processes into intelligent, automated systems.
Lead proof-of-concept initiatives for emerging tools and platforms, assessing their potential value for the university's analytics ecosystem.
Deploy current and future AI tools to reduce processing time and improve accuracy while maintaining the flexibility to adapt as new technologies emerge.
Create technology-agnostic data summarization and insight generation processes that can leverage available tools to, enable leadership to make evidence-informed decisions.
Data Architecture Partnership & Evolution:
Collaborate with the campus data warehouse team to specify, design, and optimize data structures that support multiple analytics platforms and can adapt to future technologies.
Serve as the strategic liaison between IDR and IT data services, translating complex institutional research requirements into scalable, platform-independent data solutions.
Lead the evolution of IDR's data models to support current tools (Tableau, Fabric) while designing for future flexibility, ensuring data structures can support whatever analytics platforms the university adopts.
Advocate for modern, adaptable data architecture principles that prioritize longevity and flexibility over platform specific solutions.