Job Description Summary:
The Data Management manager will lead and oversee the architecture, modeling, and management of the University’s data warehouse and data lake. This role is responsible for ensuring that data is strategically aligned with business goals and is efficiently structured, stored, and governed across the enterprise. The ideal candidate will have a strong background in data architecture, data modeling, and data warehouse management, data lake management, with a focus on optimizing the availability, quality, and security of data to support analytics and reporting initiatives.

Key Responsibilities:

Data Architecture:
Design and implement a scalable data architecture that supports business objectives and aligns with industry best practices.
Develop data integration strategies, ensuring seamless data flow from source systems to the data warehouse and/or data lake.
Define data governance standards and frameworks, ensuring consistent data management and adherence to compliance requirements.

Data Modeling:
Lead the design of conceptual, logical, and physical data models that represent business processes and information needs.
Collaborate with cross-functional teams to define data elements, relationships, and classifications for optimal business reporting and analytics.
Ensure data models are well-documented, optimized, and maintained throughout the lifecycle of projects.

Data Warehouse Management
Oversee the design, implementation, and maintenance of the enterprise data warehouse and data lake, ensuring data integrity and accuracy.
Develop processes for ETL (extract, transform, load) operations to ensure efficient data integration and transformation.
Manage data storage solutions, including cloud-based and on-premises platforms, to support BI and reporting tools.

Team Leadership & Development:
Manage and mentor a team of data architects, modelers, and data warehouse professionals, fostering a culture of continuous improvement and innovation.
Collaborate with stakeholders and customers to ensure data initiatives align with business strategies and support decision-making.
Lead efforts to stay updated on emerging data technologies and integrate innovative solutions into the data ecosystem.

This position performs other duties as assigned. The omission of specific duties does not preclude the supervisor from assigning duties that are logically related to the position.
Minimum Qualifications:
Qualified candidates will hold a Bachelor’s degree in an appropriate area of specialization plus 8 years of relevant professional experience, or, a Master’s degree or higher in a relevant area of study plus 6 years of relevant professional experience. Degree must be conferred by the start date of the position. Degree requirements may be substituted with an equivalent combination of education, training and experience.
Additional Required Licenses/Certifications/Posting Specific Minimum Qualifications:
Preferred Qualifications:
Bachelor’s degree in Computer Science, Information Systems, Data Management, or a related field (Master’s degree preferred).
Strong leadership skills with a proven track record of managing and developing high-performing data teams.
Excellent communication skills, with the ability to translate complex data concepts to non-technical stakeholders and customers
5+ years of experience in data architecture, data modeling, and data warehouse management preferred.
Proficiency in data modeling tools (e.g., ERwin, SQLDBM, etc.) and data management platforms (e.g., Snowflake, AWS, Azure, Google Cloud) is desired.
Experience with data governance frameworks, security standards, and compliance regulations is preferred.
Knowledge of SQL, Python, and other programming languages used for data manipulation and automation is desired.
Experience in higher education is highly desirable, particularly in managing data systems supporting student information systems, research data, and academic analytics is desired.
Experience with modern data platforms, including cloud data warehouses (e.g., Snowflake, Redshift, BigQuery) is desired.
Familiarity with BI tools like Tableau and Power BI is desired
Knowledge of machine learning and AI-powered analytics platforms is preferred.