Data Management Analyst I

University of South Florida•Tampa, FL

About The Position

The University of South Florida (USF) is seeking a Data Management Analyst I to join their Information Technology team. USF is a large, research-intensive public university located in the Tampa Bay region of Florida, known for its innovation and high quality of life. The IT department provides a wide range of technology services to support the university's mission. This role will focus on data management, analysis, and reporting to support various university needs.

Requirements

Bachelor's degree in information technology or a related field, with two years of experience in related positions; or a Master's degree in a directly related field.
Expertise in SQL query analysis and development for data analytics.
Proven ability to efficiently learn technical tool and process skills, e.g. data modeling, data visualization, data interpretation.
Experience with Power BI, data modeling, Azure data engineering.
Strong collaboration, communication, and presentation skills.
Strong problem solving skills and growth mindset.
Passion for empowering others, e.g. to make data-driven decisions.
Current work authorization in the United States. This position is not eligible for Visa Sponsorship.

Responsibilities

Explore, investigate and identify data relationships and mechanisms to merge various data elements across unrelated and unstructured data to create coherent data models used for analysis and providing actionable information. Work with functional areas and other subject matter experts to develop understanding of information needs and provide technical data solutions to match their needs. (40%)
Develop data reporting templates and examples using best practices for story telling and visualizations of the modeled data. Develop metadata and instructional material to improve effective use and adoption of developed data solutions. (20%)
Adapt, evolve, and test data solution components in response to changing dependencies or business needs. (15%)
Maintain and enhance data engineering flows that organize and deliver data. Develop and test analytics solutions that integrate, consolidate, and transform various structured and unstructured data. (15%)
Research and promote best practices for metadata and data analysis, modeling, and storage techniques, including flexibility, scalability, automation, security, and availability. (10%)