Lead Analytics Solutions Engineer

University of Arkansas, Fayetteville

Fayetteville, Arkansas, US
$100,000 to $115,000; not specified; university co...
Microsoft fabric development
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; University contributions to benefits

Skills & Requirements

Must-have

  • Microsoft Fabric development
  • Scalable data pipelines
  • ETL/ELT design and development
  • Data modeling and integration
  • Data quality and error handling

Nice-to-have

  • Technical leadership and mentorship
  • Cloud-based data development
  • Collaboration with stakeholders
  • Promoting data engineering best practices

Key Requirements

  • Bachelor's degree
  • Advanced ETL/ELT knowledge
  • Strong code analysis skills
  • Experience with large datasets
  • Change data capture (CDC) concepts
  • Normalization and dimensional design

Work Rights

Not specified

Tailored Resume

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