$100,000 to $115,000; not specified; not specified...
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Microsoft fabric data lakehouse and warehouse
Design scalable data pipelines
Ingest data from enterprise systems
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The University of Arkansas is seeking a Lead Analytics Solutions Engineer to provide technical leadership in designing and maintaining their cloud-based data infrastructure. The ideal candidate will have strong expertise in data engineering, specifically within Microsoft Fabric, and will contribute significantly to enterprise analytics and operational excellence.
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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 benefits package includes university contributions to health, dental, life and disability insurance, tuition waivers for employees and their families, 12 official holidays, immediate leave accrual, and a choice of retirement programs with university contributions ranging from 5 to 10% of employee salary.
Matching Summary
Match Score: 75
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The University of Arkansas is seeking a Lead Analytics Solutions Engineer to provide technical leadership in designing and maintaining their cloud-based data infrastructure. The ideal candidate will have strong expertise in data engineering, specifically within Microsoft Fabric, and will contribute significantly to enterprise analytics and operational excellence.
**
Salary
$100,000 to $115,000; Not specified; Not specified
Skills & Requirements
Must-have
Microsoft Fabric data lakehouse and warehouse
design scalable data pipelines
ingest data from enterprise systems
implement data transformation logic
data quality checks and validation
technical leadership and code reviews
Nice-to-have
collaborative service-oriented environment
promote data engineering best practices
strong problem-solving skills
Key Requirements
Bachelor's degree from an accredited institution
Advanced knowledge of ETL/ELT design
Strong code analysis, debugging, and performance optimization
Experience ingesting, transforming, and managing large datasets
Working knowledge of change data capture (CDC)
Solid understanding of design principles (normalization, dimensional design)