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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer - University of Idaho - **Company:** Another Source - **Location:** Moscow, ID, United States (Remote available) - **Experience:** Experienced - **Salary:** $79,000.0 - **Contract:** Permanent contract - **Skills:** Agile Methodology, Artificial Intelligence, Data Analysis, Automation of Tests, Cloud Computing, Software Code Optimization, Code Review, Information Systems, Information Engineering, Data Governance, Data Infrastructure, Extract Transform Load (ETL), Data Vault Modeling, Dimensional Modeling, Distributed Computing Environment, Python (Programming Language), Operational Databases, Scrum Methodology, Power BI, Standard Sql, Software Engineering, SQL Databases, Enterprise Data Management, Scripting, Cloud Platform System, Git, Data Lakes, Pyspark, Information Technology, Banner Advertisement, Data Management, Software Version Control, Data Pipelines, Databricks - **Published:** October 27, 2026 - **Apply:** https://www.careerbuilder.com/job-details/data-engineer-university-of-idaho-moscow-id--9e9246f2-9c8c-41c1-92a1-b213018e4a92 ## About the Role Python Programming/Scripting Language, SQL (Structured Query Language), Cloud Computing, Problem Solving Skills, Information Technology & Information Systems, Technical Recruiting, Research Grants, Artificial Intelligence (AI), Data Collection, Finance, * Two or more 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 bachelor's degree. Preferred Qualifications * Three or more 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 working 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 working 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. ## Description Are you a data engineer who enjoys building solutions from the ground up? Do you want to work with modern cloud technologies while helping shape the future of data at a major research university? This is an opportunity to join the University of Idaho at the beginning of a significant technology transformation. As a Data Engineer, you'll play a hands-on role in designing and developing the university's enterprise data lakehouse, creating the pipelines, data models, and trusted data products that will power institutional decision-making for years to come. Rather than simply maintaining existing systems, you'll help establish the architecture, engineering practices, and foundational capabilities of a growing enterprise data platform. You'll work with Databricks, Delta Lake, Python, SQL, and cloud technologies while collaborating with technical leaders, analysts, and stakeholders across the university. Working alongside the Technical Product Manager for Enterprise Data and Data Governance Manager, you'll have the opportunity to influence how data is structured, governed, and delivered across academic and administrative functions. For someone who enjoys solving complex problems, working with emerging technologies, and seeing the direct impact of their work, this role offers an opportunity to build something meaningful. Your Contribution Will Likely Include Data Pipeline Development & Engineering (40%) * Design, build, and maintain reliable data ingestion pipelines that connect enterprise systems, including Banner/Ellucian ERP and other institutional data sources. * Develop scalable data transformations using medallion architecture (bronze, silver, and gold layers) to turn raw information into trusted, analytics-ready data products. * Write efficient, maintainable Python and SQL code while applying modern software engineering practices, including version control, code reviews, and modular development. * Partner with the Technical Product Manager to translate business needs into practical engineering solutions and contribute to agile planning and delivery. * Troubleshoot pipeline failures, integration challenges, and data quality issues to maintain reliable access to institutional information. Data Platform Support & Operations (25%) * Help operate and optimize the university's 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 that improve confidence in institutional reporting. * Develop operational documentation, troubleshooting guides, and platform procedures that support long-term sustainability. * Contribute engineering insights to platform optimization, capacity planning, and infrastructure decisions. Data Modeling & Product Development (20%) * Collaborate with institutional analysts, data consumers, and business partners to design data models that make information easier to access, understand, and use. * Create dimensional models, aggregated datasets, and curated data products that support reporting, analytics, and downstream applications. * Help establish data modeling standards, naming conventions, and documentation practices across the enterprise lakehouse. * Explore emerging Databricks capabilities, including Delta Live Tables, Lakeflow Connect, and AI/BI Genie, to identify opportunities for innovation and platform improvement. Collaboration, Documentation & Continuous Learning (15%) * Work within a collaborative, agile technology team, participating in sprint planning, technical discussions, and solution design. * Build relationships with data stewards, analysts, and university stakeholders to understand their needs and identify opportunities to improve data accessibility. * Create clear, useful documentation for pipelines, data products, and integration patterns. * Stay current with developments in data engineering, cloud infrastructure, and Databricks technologies, sharing knowledge and ideas with colleagues.