Data Engineer III

Data Engineer III

Job Summary

Data Engineer III

Join the Utah Data Coordinating Center (DCC) as a Data Engineer, where your work will directly enable innovative clinical research at the University of Utah and across national partners. You'll lead the design of scalable data systems, define and enforce architecture standards, and work alongside software developers, data analysts, and research teams to ensure our platforms evolve with the needs of scientific discovery.

This is a growth-focused role ideal for someone who thrives in a collaborative, mission-driven environment. The Utah DCC supports large-scale health data infrastructure that underpins national emergency response, clinical registries, and federal research initiatives.

Establish project teams and provide overall direction for technical projects from initiation through to delivery. Perform project requirements, estimation, and budget management. Formulate project scope and delivery strategies and establish milestones/schedules. Maintain and report project status and monitor progress of all team members. Gather required data from end-users to evaluate objectives, goals, and scope to create technical specifications. Serve as liaison between technical and non-technical departments in order to ensure that all targets and requirements are met.

Keep leadership informed of key issues that may impact project completion, budget, or other results.

The Utah DCC offers a career ladder for Data Engineers and provides growth and professional development opportunities.

This position is not eligible for work visa sponsorship.

To learn more about the Utah DCC visit (Use the "Apply for this Job" box below)./UtahDCC

Job Responsibilities or

Essential Functions:

As a Data Engineer, your responsibilities will include:

1. Design, develop, and maintain database architecture following industry best practices

Design and implement scalable, secure, and high-performing database solutions aligned with industry standards and architectural best practices. This includes data modeling (conceptual, logical, and physical), schema design, indexing strategies, performance tuning, backup and recovery planning, and ensuring data integrity and consistency. Establish governance standards, naming conventions, version control processes, and documentation to support maintainability, reliability, and long-term scalability across environments.

2. Build, optimize, and maintain scalable data pipelines

Design, develop, and orchestrate reliable, high-performance data pipelines from initial data ingestion through final delivery. This includes data pipeline development, orchestration, transformation logic, and supporting data models optimized for analytics and operational workloads.

3. Develop and optimize data processing and automation code

Design, implement, and maintain robust code for data extraction, transformation, integration, and analysis using appropriate languages and frameworks. Optimize performance, ensure data accuracy, and uphold high standards for code quality, reliability, and maintainability in alignment with software and data engineering best practices.

4. Drive continuous improvement and innovation in cloud data technologies (AWS-focused)

Stay current with emerging data engineering technologies, industry trends, and evolving AWS services to continuously enhance platform capabilities and architectural standards. Evaluate and adopt appropriate AWS services (e.g., S3, Glue, Lambda, Redshift, RDS, EMR, Step Functions, Lake Formation) to improve scalability, performance, cost efficiency, and reliability. Balance innovation with operational excellence by maintaining and optimizing existing services, enforcing best practices, and ensuring stable, secure, and high-performing production environments.

5. Collaborate with business partners to develop scalable data solutions

Partner with internal teams and external stakeholders to design and deliver innovative data solutions that support evolving business needs. This includes developing and exposing data through APIs, building and maintaining multi-dimensional cubes and semantic models, enabling secure data sharing, and creating reusable data services. Translate…