Data Engineer, OIT

University of Idaho Careers; Moscow (ID); Híbrido; USD 85.000 - 100.000; Jornada completa

Descripción de la vacante

University of Idaho is seeking a Data Engineer to design, develop, and operate the university’s enterprise data platform on a Databricks lakehouse. The role focuses on building data pipelines, transformations, and data products that power institutional analytics and decision-making.

You will work closely with the Technical Product Manager for Enterprise Data, Data Governance, and campus stakeholders to ingest, transform, and serve data across the lakehouse.

Formación

• Two years of experience in data engineering or a closely related technical role.
• Demonstrated experience writing Python or SQL to process, transform or analyze data.
• Experience building or supporting data pipelines or ETL/ELT workflows in a production environment.

Responsabilidades

• Building and maintaining data ingestion pipelines from enterprise source systems
• Transforming raw data into clean, structured data products using medallion architecture principles
• Supporting the Databricks lakehouse platform including Unity Catalog administration and pipeline monitoring
• Collaborating with data consumers, analysts and product managers to define and deliver data products
• Documenting data pipelines, data models and platform runbooks
• Other duties as assigned

Conocimientos

Python

SQL

Data pipelines

Educación

Bachelor’s degree in Computer Science, Information Technology, Management of Information Systems or related field

Herramientas

Databricks

Unity Catalog

Delta Lake

Descripción del empleo

Appointment Information

Working Title: Data Engineer

Division/College: 3927-EA ENTERPRISE APPLICATIONS

Department: 655-EA Integration and Development

Location: Moscow

Location Details: Flexible Work Location (On-Campus, Hybrid, or U.S. Remote) available

FTE: 1

Advertising Pay Range: $85,000.00 +DOE

Is this position contingent on work and/or funding: False

FLSA Status: Exempt

Type of Appointment: Full Fiscal Year

Position Overview:

The Data Engineer supports the design, development, and operation of the university’s enterprise data platform. This position is focused on building the data pipelines, transformations and data products that power institutional analytics and decision-making on the lakehouse platform.

The Data Engineer will work closely with the Technical Product Manager for Enterprise Data, Data Governance Manager and institutional stakeholders to ingest, transform and serve data across the university’s lakehouse. The position offers meaningful hands‑on work with Databricks, Delta Lake, and cloud infrastructure in a collaborative, mission‑driven environment.

Duties may include:

• Building and maintaining data ingestion pipelines from enterprise source systems
• Transforming raw data into clean, structured data products using medallion architecture principles
• Supporting the Databricks lakehouse platform including Unity Catalog administration and pipeline monitoring
• Collaborating with data consumers, analysts and product managers to define and deliver data products
• Documenting data pipelines, data models and platform runbooks
• Other duties as assigned

Required Experience:

• Two years of experience in data engineering, software development or a closely related technical role
• Demonstrated experience writing Python or SQL to process, transform or analyze data
• Experience building or supporting data pipelines or ETL/ELT workflows in a production environment

Required Education:

• Bachelor’s degree in Computer Science, Information Technology, Management of Information Systems or a related field; four additional years of experience (for a total of six years) may substitute for a Bachelor’s Degree

Required Other:

• None

Additional Preferred:

• Three (3) or more years of experience in data engineering or a closely related technical field
• Databricks Certified Data Engineer Associate or Professional certification
• Bachelor’s degree or higher in a technical field
• Experience with:
  • Cloud-based data lakehouse platforms (Databricks preferred)
  • PySpark or distributed data processing frameworks
  • Data modeling patterns including medallion architecture, dimensional modeling or data vault concepts
  • ERP data structures in student, HR or finance domains (Banner/Ellucian preferred)
  • Cloud platforms
  • Source control and collaborative development workflows (Git, pull request reviews)
  • Data quality frameworks and tooling (e.g., dbt tests or similar)
  • BI platform connectivity and supporting analytical consumers (Power BI or similar)
  • Higher education technology environments and constituent-sensitive data
  • Agile development methodologies and sprint-based delivery

Physical Requirements and Working Conditions:

• None

Posting Information

Open Until Filled:

True

Visa Sponsorship:

No

Degree Requirement Timeline:

Degree required at time of hire