Data Engineer - University of Idaho

Another Source • Moscow, ID

14h

About The Position

The University of Idaho is recruiting a Data Engineer for its Office of Information Technology in Moscow, Idaho. This role offers potential hybrid or remote flexibility, depending on the candidate and institutional needs. The university is launching a multi-year data modernization initiative to transform how institutional data is collected, managed, and used. The Data Engineer will help establish an enterprise data lakehouse and the architecture, engineering practices, pipelines, data models, and trusted data products that support institutional decision-making, analytics, and emerging AI applications.

The position involves hands-on work with Databricks, Delta Lake, Python, SQL, and cloud technologies. The Data Engineer will collaborate with technical leaders, analysts, data stewards, and university stakeholders, including the Technical Product Manager for Enterprise Data and the Data Governance Manager. The role also includes supporting platform operations and governance, developing data models and curated products, documenting solutions, and contributing to agile planning and continuous learning.

Requirements

• At least two years of experience in data engineering, software development, or a closely related technical role.
• Demonstrated experience using Python or SQL to process, transform, or analyze data.
• Experience developing or supporting production data pipelines, including ETL/ELT workflows.
• Bachelor's degree in Computer Science, Information Technology, Management Information Systems, or a related field; four additional years of relevant experience, for six years total, may substitute for the degree.

Nice To Haves

• At least three years of experience in data engineering or a related technical field.
• Experience with cloud-based data platforms, particularly Databricks, Delta Lake, or similar lakehouse technologies.
• Familiarity with PySpark or other distributed data processing frameworks.
• Understanding of data modeling approaches such as medallion architecture, dimensional modeling, or data vault.
• Experience with enterprise ERP data, particularly Banner/Ellucian or systems supporting student, HR, or financial operations.
• Experience with cloud infrastructure, Git, pull request reviews, and collaborative development practices.
• Familiarity with data quality frameworks, automated testing, and BI tools such as Power BI.
• Experience in higher education technology environments or working with sensitive institutional data.
• Familiarity with agile development methodologies and sprint-based delivery.
• Databricks Certified Data Engineer Associate or Professional certification.

Responsibilities

• Design, build, and maintain reliable data ingestion pipelines connecting enterprise systems, including Banner/Ellucian ERP and other institutional data sources.
• Develop scalable data transformations using bronze, silver, and gold medallion architecture layers.
• Write efficient, maintainable Python and SQL code using version control, code reviews, and modular development practices.
• Partner with the Technical Product Manager to turn business needs into engineering solutions and contribute to agile planning and delivery.
• Troubleshoot pipeline failures, integration challenges, and data quality issues.
• Operate and optimize the Databricks lakehouse environment, monitoring pipelines, compute resources, and platform performance.
• Support Unity Catalog administration, including data organization, access controls, and governance-aligned configurations.
• Build automated data quality checks and validation processes.
• Develop operational documentation, troubleshooting guides, and platform procedures.
• Contribute engineering insights to platform optimization, capacity planning, and infrastructure decisions.
• Collaborate with analysts, data consumers, and business partners to design accessible and useful data models.
• Create dimensional models, aggregated datasets, and curated data products for reporting, analytics, and downstream applications.
• Help establish data modeling standards, naming conventions, and documentation practices for the enterprise lakehouse.
• Explore Databricks capabilities such as Delta Live Tables, Lakeflow Connect, and AI/BI Genie to identify opportunities for innovation and improvement.
• Participate in sprint planning, technical discussions, and solution design as part of a collaborative agile technology team.
• Build relationships with data stewards, analysts, and university stakeholders to understand needs and improve data accessibility.
• Document pipelines, data products, and integration patterns.
• Keep current with data engineering, cloud infrastructure, and Databricks technologies, sharing knowledge and ideas with colleagues.

Benefits

• Comprehensive employee benefits program supporting health, financial well-being, and long-term professional success.
• Professional development and opportunities to grow expertise through emerging technologies and collaborative problem-solving.
• Potential hybrid or remote work arrangements, depending on the candidate and institutional needs.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level