$100,000 to $115,000; not specified; university co...
Not specified
Microsoft fabric development
Scalable data pipelines
Etl/elt design and development
The University of Arkansas is seeking a Lead Analytics Solutions Engineer to provide technical leadership in designing and developing cloud-based data solutions, primarily utilizing Microsoft Fabric. The ideal candidate will have advanced knowledge in data engineering, with specific expertise in ETL/ELT processes and large dataset management
Job Summary
The Lead Analytics Solutions Engineer provides technical leadership for the design, development, and ongoing operation of the University’s cloud-based data lake and warehousing environment, with a primary focus on Microsoft Fabric.
This role is responsible for building scalable, reliable data pipelines and integration solutions that enable enterprise analytics and reporting across academic and administrative units.
The University of Arkansas offers a vibrant work environment and a workplace culture that promotes a healthy work-life balance, with a comprehensive benefits package.
Matching Summary
Match Score: 85
The University of Arkansas is seeking a Lead Analytics Solutions Engineer to provide technical leadership in designing and developing cloud-based data solutions, primarily utilizing Microsoft Fabric. The ideal candidate will have advanced knowledge in data engineering, with specific expertise in ETL/ELT processes and large dataset management.
Salary
$100,000 to $115,000; Not specified; University contributions to health, dental, life and disability insurance, tuition waivers, 12 holidays, immediate leave accrual, and retirement programs
Skills & Requirements
Must-have
Microsoft Fabric development
Scalable data pipelines
ETL/ELT design and development
Data modeling and integration strategies
Data quality and error handling
Nice-to-have
Technical leadership and mentorship
Cloud-based data development
Collaborative service-oriented environment
Key Requirements
Bachelor's degree from an accredited institution
Advanced ETL/ELT knowledge
Strong code analysis and debugging skills
Experience with large, complex datasets
Change data capture (CDC) knowledge
Normalization and dimensional design understanding