$100,000 to $115,000; not specified; benefits elig...
Microsoft fabric data lake and warehousing
Scalable data pipelines
Etl/elt design and development
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
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
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.
Salary
$100,000 to $115,000; Not specified; Benefits eligible
Skills & Requirements
Must-have
Microsoft Fabric data lake and warehousing
Scalable data pipelines
ETL/ELT design and development
Data transformation logic
Data quality and reliability
Code reviews and technical leadership
Nice-to-have
Collaborative service-oriented environment
Promoting 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 skills
Experience ingesting, transforming, and managing large datasets
Working knowledge of change data capture (CDC)
Solid understanding of normalization and dimensional design