Data Engineer - University of Idaho

Another Source • Moscow, ID

12d

About The Position

The University of Idaho’s Office of Information Technology is hiring a Data Engineer to help launch a multi-year data modernization initiative. The role will contribute to the design and development of an enterprise data lakehouse and establish foundational architecture, engineering practices, and platform capabilities. The resulting data pipelines, models, and trusted data products will support institutional decision-making, analytics, research, operations, and emerging AI applications.

The Data Engineer will work with Databricks, Delta Lake, Python, SQL, and cloud technologies, collaborating with technical leaders, analysts, data stewards, and stakeholders across the university. The role includes developing and operating pipelines and the lakehouse environment, creating data models and curated products, and contributing to data governance, documentation, platform optimization, and continuous improvement. The position is based in Moscow, Idaho, with hybrid or remote arrangements potentially available depending on the candidate and institutional needs.

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 (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 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 transformations using medallion architecture (bronze, silver, and gold layers) to create trusted, analytics-ready data products.
• Write maintainable Python and SQL code using modern software engineering practices, including version control, code reviews, and modular development.
• 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 usable 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 across the enterprise lakehouse.
• Explore Databricks capabilities, including 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 within a collaborative agile team.
• Build relationships with data stewards, analysts, and university stakeholders to understand needs and improve data accessibility.
• Document pipelines, data products, and integration patterns.
• Stay current with data engineering, cloud infrastructure, and Databricks developments, and share knowledge 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