Data Engineer II

University of South Florida•Tampa, FL

6d•$79,684 - $103,000

About The Position

The Data Engineer II collaborates with faculty, operational staff, business users, and other stakeholders to develop, manage, and optimize datasets, reports, data pipelines, and systems supporting programs and projects at HII, with particular emphasis on the Florida Parkinson’s Disease Registry. As part of the Data Engineering team, the role supports the full data lifecycle, including data integration, curation, quality assurance, reporting, and data sharing. The position applies professional expertise to manage and integrate data from diverse sources, develop and operationalize data solutions, and support program and project deliverables. It helps ensure data integrity, standardization, security, and compliance with applicable data governance requirements, while identifying opportunities to improve efficiency, automation, and reuse of data processes and solutions.

Requirements

Bachelor’s degree in Computer Science, MIS, or another field involving software and analytical training, and two years of relevant work experience; or a bachelor’s degree in any field and three years of relevant work experience.
Applicants must meet all employment eligibility requirements in the United States; the position is not eligible for visa sponsorship.

Nice To Haves

Master’s degree and one year of relevant work experience; or a combination of six years of relevant work experience and validated training.
Preparation for a relevant IT certification, validated through certification requirements and documentation of completion, is considered related training.

Responsibilities

Develop, implement, and maintain complex data processes, programs, and pipelines to integrate, transform, cleanse, and consolidate data from diverse sources for reporting, analytics, and operational use.
Create and maintain SAS, SQL, and related data processing programs to extract, subset, transform, summarize, and validate data from large and complex databases and institutional systems.
Design and implement data models, data structures, and integration processes that support reliable analytics, reporting, and data sharing; assist with new data acquisition, exploration, standardization, and integration.
Develop, review, enhance, publish, and schedule reports, dashboards, and analytical outputs to monitor data acquisition, data quality, project and program status, and other key performance measures.
Design and maintain processes that promote data integrity, completeness, accuracy, and consistency across datasets, reports, dashboards, and other data products.
Work with faculty, operational staff, business users, and other stakeholders to understand objectives, analyze functional and data requirements, and translate needs into technical designs, prototypes, data models, reports, and analytical solutions.
Collaborate with external institutions and agencies to support project execution, data exchange, integration, and resource sharing.
Apply best practices to the development, implementation, documentation, and maintenance of data programs, pipelines, systems, and analytical solutions while adhering to institutional data governance, security, privacy, and data management requirements.
Maintain the integrity, reliability, and reproducibility of analysis datasets, data models, documentation, programming code, and other technical deliverables; document systems, processes, and workflows and contribute to standard operating procedures.
Identify and implement opportunities to improve data processing, integration, reporting, automation, standardization, and reuse.
Coordinate activities with team members and stakeholders to support timely completion of project and program deliverables; communicate progress, timelines, accomplishments, risks, and issues to management, including proposed mitigation strategies.
Develop and maintain domain expertise in complex enterprise applications, institutional data systems, data processing technologies, and business intelligence tools.