Director of Data, Automation, and Intelligence Services
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Lead the design, development, and management of enterprise data infrastructure and analytics platforms Oversee data pipelines, data modeling, and reporting solutions that support institutional decision-making Ensure data accuracy, consistency, and accessibility across systems and stakeholders Partner with stakeholders to translate business needs into data and reporting solutions Direct the design and implementation of integrations across enterprise applications Lead the development of automated workflows that reduce manual processes and improve operational efficiency Ensure integration reliability, scalability, and alignment with institutional architecture Oversee the delivery of dashboards, reports, and analytical tools for academic and administrative units Promote self-service reporting capabilities while maintaining governance and data integrity Drive the use of data to support planning, performance measurement, and strategic initiatives Lead the evaluation and implementation of AI-enabled tools and solutions that enhance decision-making and efficiency Identify opportunities for advanced analytics, automation, and intelligent insights across the institution Lead, coach, and develop a multidisciplinary team of data engineers, analysts, and integration specialists Serve as a trusted advisor and liaison to campus partners on data, reporting, and automation needs Promote cross
- ITS collaboration and consistent practices Contribute to multi-year data and analytics strategies aligned with institutional priorities Support governance for data management, system integrations, and responsible use of data and AI Establish and track key performance indicators related to data quality, reporting adoption, and automation impact Identify and implement improvements that enhance data reliability, efficiency, and user experience Performs other duties as assigned
Qualifications
Bachelor’s degree in information technology, data science, computer science, or related field Progressive experience (typically 7–10 years) in data, analytics, integration, or related IT functions Experience leading data engineering, business intelligence, or enterprise integration initiatives Strong understanding of data architecture, reporting platforms, and automation tools Demonstrated ability to lead teams and collaborate with technical and nontechnical stakeholders Excellent communication, problem-solving, and leadership skills Preferred Master’s degree in a related field Experience in higher education or similarly complex organizations Experience with data platforms, ETL / ELT processes, and analytics tools Familiarity with integration technologies (e.g., APIs, middleware) Experience with AI/advanced analytics tools and governance considerations Experience with enterprise reporting and data visualization platforms
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