The University of Arkansas at Little Rock is seeking a Data Engineer I for the COSMOS Research Center, responsible for managing and analyzing data to support research projects. The ideal candidate will have a bachelor's degree in Computer Science or a related field and possess skills in data analysis, programming, and data pipeline management
Job Summary
The Project/Program Specialist (Data Engineer I) will collect, manage, and convert raw data into usable information for analytics and decision-making.
This role requires comprehensive data analysis skills, developing and maintaining datasets, improving data quality and efficiency through leveraging data systems and pipelines, interpreting trends and patterns of data, creating complex data reports, and building algorithms and prototypes.
The Project/Program Specialist (Data Engineer I) will collaborate with researchers, participate in research projects, and interact with other developers at the COSMOS research center and partner organizations to achieve the best possible performance metrics across various projects.
Matching Summary
Match Score: 75
The University of Arkansas at Little Rock is seeking a Data Engineer I for the COSMOS Research Center, responsible for managing and analyzing data to support research projects. The ideal candidate will have a bachelor's degree in Computer Science or a related field and possess skills in data analysis, programming, and data pipeline management.
Salary
$60,000 annually
Skills & Requirements
Must-have
Collect and analyze raw data
Develop and maintain datasets
Improve data quality and efficiency
Design and manage data pipelines
Interpret trends and patterns of data
Build algorithms and prototypes
Nice-to-have
Contribute to cutting-edge research
Collaborate with researchers and developers
Leverage data systems and pipelines
Key Requirements
Bachelor's degree in Computer Science, Information Science, or related discipline
Proficiency in programming/scripting languages (e.g., Java and Python)
Proficiency in SQL database design
Proficiency in data models, data pipelines, ETL processes, data stores, data mining, and segmentation techniques
Proficiency in numerical, analytical, and data security skills