Data Engineer 4 - Enterprise Data and Analytics - FT - Remote

UCI Health Data Engineer

UCI Health is one of California's largest academic health systems and the clinical enterprise of the University of California, Irvine. Established on July 1, 1976, UCI Health has grown into a 1,461-bed health system that includes UCI Health - Orange, UCI Health - Irvine, four Community Network hospitals and a growing network of ambulatory care centers across Orange and Los Angeles counties. As Orange County's only academic health systems, UCI Health is home to the only National Cancer Institute-designated comprehensive cancer center based in the county, the region's only American College of Surgeons-verified Level I adult and Level II pediatric trauma center, American College of Emergency Physicians Gold Level 1 Geriatric Emergency Department and a nationally recognized regional burn center verified by the American Burn Association. Powered by UC Irvine, UCI Health serves 5.6 million people across Orange County, western Riverside County and southeast Los Angeles County through excellence in patient care, research and medical education.

Your Role on the Team

Position Summary: The incumbent will be responsible for designing, building, and maintaining governed data models and enterprise reporting and analytics solutions supporting quality metrics, regulatory requirements, and clinical, operational, and research needs, using Epic-based electronic health data as well as other healthcare data sources. The incumbent will work on a multidisciplinary team of analytics engineers, data engineers, data architects, and BI developers within the Enterprise Data and Analytics Department and will collaborate with other institutions across University of California Health. The incumbent will use tools in use at UCI Health, including Microsoft Fabric, data transformation and governance tools, Git-based version control, and Microsoft Power BI, to deliver high-quality, reliable, and accurate analytics products. This position requires treating data transformation as a software engineering discipline, in which version control, code review, automated testing, modular data modeling, and documentation are integral to the work rather than supplementary tasks. The incumbent will help transform a traditional report-writing analytics function into a modern data product organization, and will partner closely with end users to understand and anticipate how data models and structures can proactively solve clinical, operational, and research challenges.

What It Takes to be Successful

Required Qualifications: Strong written and verbal communication skills Must possess the skill, knowledge and ability essential to the successful performance of assigned duties Must demonstrate customer service skills appropriate to the job Experience maintaining technical documentation and reviewing code within a centralized code repository Excellent written and verbal communication skills in English Bachelor's degree in Computer Science (or related field) or equivalent work experience Ability to maintain a work pace appropriate to the workload Ability to establish and maintain effective working relationships across the Health System 3+ years with SQL or NoSQL databases and data warehousing technologies 3+ years hands-on experience with ETL Tools or Business Intelligence 2+ years of hands-on experience creating data pipelines using Python 2+ years hands-on experience as a Data Engineer Preferred Qualifications: Knowledge of University and Medical Center organizations, policies, procedures and forms Experience working with data governance and a data catalog platform (e.g., Collibra) Experience performing unit tests and troubleshooting complex issues/efforts with other team members or cross divisional teams Experience creating and optimizing data pipelines capable of ingesting and integrating data from multiple heterogenous sources with advanced analytics capabilities (e.g., NLP, ML) Ability to work in agile team structure 2+ years of hands-on experience in pipeline orchestration tools, logging, monitoring & alerting, troubleshooting, and automated testing & deployments (CI/CD), preferably using cloud-based technologies (e.g., Azure, Databricks, AWS)