IT DATA ANALYTICS ENGINEER

The College of Western Idaho is looking for an IT Data Analytics Engineer who thrives at the intersection of data transformation, data engineering, and modern data platform development. This is not a report-writing or dashboard development role. It is a hands-on engineering position focused on building and maintaining a data pipeline that supports reliable, consistent analytics across CWI.

You’ll work at the center of CWI’s Microsoft Fabric environment, transforming mirrored operational data from Azure SQL Managed Instance into well-structured, analytics-ready datasets that serve the College’s data and analytics team. Your work will serve as a critical technical bridge between source systems and data analysts, improving the quality, reliability, and usability of institutional data across the college.

Essential Functions:

Analytics Engineering & Data Preparation

• Develop and maintain Microsoft Fabric notebooks to transform and curate operational data for analytics consumption

• Working with the data warehouse architect and data analysts, create and maintain curated tables, provide technical expertise, and optimize the data pipeline for efficiency and consistency.

• Apply SQL, Spark, and/or Python transformation patterns to produce clean, validated, analytics-ready datasets

• Validate data quality and consistency across curated data layers, documenting findings and resolutions. Work with enterprise application team members to map application data entry and data flow through centrally managed systems.

• Validate enterprise application data against systems of record, developing an understanding of how the data is defined and used within those systems.

• Collaborate with information technology application team members and analysts to support system reporting and internal IT reporting needs. Partner with the data warehouse architect to align workspace design with the foundational data warehouse architecture, ensuring workspaces are effectively built to support the data and analytics team.

Maintain documentation and ensure standards compliance across all analytics engineering deliverables

Fabric Workspace Support

• Support assigned Microsoft Fabric workspaces within established governance and architectural standards

• Organize and manage analytics assets across Development, Test, and Production environments

• Create workspaces and apply workspace access controls as directed by platform and governance owners

• Work with data governance to implement uniform transformations and data cleansing across the data pipeline in alignment with approved business rules

• Identify, triage, and escalate platform or data issues as needed to maintain pipeline and workspace reliability

GitHub Enterprise & Collaboration

• Version control all notebooks and transformation assets using GitHub Enterprise

• Follow pull request and peer review practices to ensure code quality, consistency, and auditability

• Support controlled promotion of analytics assets across environments through established CI/CD patterns

• Partner with information technology team and business units to align on data contracts and delivery expectations

Do you have experience in Version control systems?, Do you have a Bachelor’s degree?, * Bachelor’s degree in Computer Science, Information Systems, Data Analytics, or a related field, or equivalent professional experience

• 3-5 years of professional experience in analytics engineering, data engineering, or business intelligence roles

• Hands-on experience with Microsoft Fabric analytics workloads, including notebooks, lakehouses, and curated datasets

• Strong SQL skills with working knowledge of Spark and/or Python for data transformation workflows

• Experience using Git or GitHub Enterprise, pull requests, branching strategies, and version-controlled development workflows

• Solid understanding of analytical data modeling principles, including dimensional modeling and layered data architecture

• Strong written and verbal communication skills, you can document complex data logic clearly for both engineers and non-technical stakeholders