$100,000 to $115,000; not specified; not specified...
Microsoft fabric data lakehouse and warehouse
Design and develop scalable data pipelines
Ingest data from enterprise systems
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.
Partnering closely with data architects, analysts, and campus stakeholders, the role shapes data models and system architecture while also mentoring peers, conducting code reviews, and promoting data engineering best practices.
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; Not specified
Skills & Requirements
Must-have
Microsoft Fabric data lakehouse and warehouse
design and develop scalable data pipelines
ingest data from enterprise systems
implement robust data transformation logic
enforce data quality checks and validation
technical leadership and code reviews
Nice-to-have
collaborative service-oriented environment
promote data engineering best practices
balance hands-on development with leadership
Key Requirements
Bachelor's degree from an accredited institution
Advanced knowledge of ETL/ELT design
Strong code analysis, debugging, and optimization skills
Experience managing large and complex datasets
Working knowledge of change data capture (CDC)
Solid understanding of design principles (normalization, dimensional)