"Director of Data Management and Reporting (UFA)"

Position Summary

Rutgers, The State University of New Jersey is seeking a Director of Data Management and Reporting (UFA) for University Finance & Administration.

The Director of Data Management & Reporting is an experienced team leader who leads the modernization of UFA's data foundation, ensuring secure, trusted, and analytics-ready data that supports financial and administrative decision-making across UFA and its stakeholders throughout Rutgers. Reporting to the Chief Data Officer (CDO), this role executes UFA's data management and reporting vision by providing strong technical and functional leadership in data modeling, multi-source data integration, and the design of data structures that support UFA's operational and analytics needs.

In close collaboration with OIT, this role assesses UFA's data and reporting needs and contributes UFA's functional and technical requirements to the design and implementation of a modern, scalable data platform. The platform will enable strong governance, cross-domain integration, and operational/ERP reporting while aligning with the Office of Information Technology's (OIT) technology standards, platform guidance, and integration frameworks.

This role serves as UFA's data and reporting partner to OIT, ensuring institutional alignment while maintaining the technical depth required to guide UFA's internal implementation. The Director brings recent, hands-on experience with modern data platforms, data modeling, and ELT/ETL patterns, enabling UFA to deliver certified, analytics-ready datasets for operational reporting and to support downstream analytics used across Rutgers.

Among the key duties of this position are the following:

• Provides technical leadership for UFA's data environment, including conceptual/logical/physical data modeling, warehouse/lake structures, semantic layers, and reusable data products, working collaboratively with OIT to ensure architectural and security alignment.
• Contributes to integration standards (ETL/ELT) across systems (e.g., Oracle ERP/HCM, Banner) by advising on reliability, scalability, performance tuning, observability, and secure data movement, in coordination with OIT integration teams.
• Establishes and promotes UFA's internal standards for modeling, transformation logic, views/materialized views, semantic layers, and certified datasets that support operational reporting and downstream analytics while ensuring consistency with enterprise guidance.
• Translates business needs into technical requirements specific to UFA and contributes to sequencing modernization priorities under the direction of the CDO and in partnership with OIT.
• Evaluates UFA's data and reporting needs and determines how they can be best supported through institutional data platforms (e.g., Oracle FDI, cloud data warehouse/lakehouse patterns), ensuring alignment with OIT's cloud, integration, and security frameworks through close partnership with OIT.
• Applies strong hands-on expertise in SQL, optimization, indexing, normalization, modern ELT/ETL approaches, and cloud-scale data platform capabilities to guide internal design choices, mentor staff, and support the adoption of modern patterns in close collaboration with OIT.
• Partners with OIT, functional leaders, and stakeholders across all campuses and central units to translate business needs into data, platform, modeling, and governance requirements; promotes adoption of modern data practices and strengthens data literacy across UFA.
• Oversees the delivery and operating model for UFA's data management and reporting function–including roadmaps, Jira/ServiceNow workflows, release/change management–ensuring predictable, transparent, and timely outcomes.
• Leads and develops the team by modeling a collaborative, accountable, and service-oriented culture; sets goals, coaches performance, builds capabilities, reinforces documentation, and establishes succession plans.
• Serves as the escalation point for complex reporting, integration, data modeling, or governance issues, recommends modernization options (e.g., platform capabilities, vendor tools, buy vs. build decisions) aligned with institutional strategy and the CDO's direction.
• Provides seasoned leadership and hands-on technical experience in modern data platforms, data modeling, and ELT/ETL practices to strengthen staff capabilities and ensure consistent, high-quality outcomes across UFA and the stakeholders it serves.
• Operationalizes UFA governance decisions—including business glossary, data definitions, metadata standards, lineage documentation, access controls, stewardship roles, and classification/retention requirements—ensuring compliance with FERPA, GLBA, and institutional policies.
• Establishes and promotes data-quality controls (e.g., validation, reconciliation, profiling) across source, staging, and presentation layers; publishes quality metrics, partners with data owners and stewards on remediation, and monitors progress.
• Oversees Oracle ERP/HCM reporting (OTBI, BI Publisher, OAC, Smart View) and associated SQL processes; manages intake, prioritization, SLAs, user acceptance testing, quality assurance, and release/change management for UFA's operational reporting needs, in coordination with OIT, supporting thousands of users across all Rutgers campuses who rely on accurate, consistent, and timely ERP reporting.
• Oversees Tableau-based operational reporting (non-dashboard, non-analytical reports) by maintaining governed views/materialized views and certified Tableau data sources that support transactional, compliance, and operational use cases; ensure adherence to KPI definitions, metadata standards, and governance decisions.
• Enables operational self-service reporting by curating certified datasets and semantic layers aligned with day-to-day business needs; provides guidance to operational users and ensures that curated datasets appropriately support downstream analytics developed by other analytics teams

Minimum Education and Experience:

• Bachelor's degree in Information Systems, Computer Science, Data Analytics, or a related field.
• At least ten (10) years of progressive experience in data management, data engineering, data architecture, or enterprise analytics, including recent (within the last 5–7 years) hands-on work with cloud-scale data platforms, modern integration frameworks, and data modeling.

Equipment Utilized:

• Standard office and meeting technologies (computer, telephone, videoconferencing tools).
• Enterprise data platforms and reporting environments, including:
• SQL Server–based environments (e.g., SSIS/Visual Studio, SQL Server Management tools)
• Oracle Cloud–based environments (e.g., Oracle ERP/HCM, OTBI, BI Publisher, OAC, Smart View)
• Cloud data platforms and related services (e.g., Oracle Cloud Infrastructure (OCI), Azure, AWS)
• Data warehousing and integration tools, such as Oracle FDI, SSIS/Visual Studio, Informatica, or equivalent modern ELT/ETL technologies.
• Data modeling, SQL development, and analytics tools, including SQL client tools, Python-enabled environments, and Tableau for operational reporting.
• Collaboration and project management tools (e.g., Jira/ServiceNow, Teams, SharePoint).