Data Engineers

Priority Review Date (Note - Posting may close at any time)

Design, build, implement, and maintain data processing pipelines for the extraction, transformation, and loading (ETL) of data from a variety of data sources. Develop robust and scalable solutions that transform data into a useful format for analysis, enhance data flow, and enable end users to consume and analyze data faster and easier. Write complex SQL queries to support analytics needs. Evaluate and recommend tools and technologies for data infrastructure and processing.

Collaborate with engineers, data scientists, data analysts, product teams, and other stakeholders to translate business requirements to technical specifications and coded data pipelines. Work with tools, languages, data processing frameworks, and databases such as R, Python, SQL, Mongo

DB, Redis, Hadoop, Spark, Hive, Scala, Big Table, Cassandra, Presto, Strom. Work with structured and unstructured data from a variety of data stores, such as data lakes, relational database management systems, and/or data warehouses.

Work collaboratively with end-users including researchers to recommend strategies for problem analysis, study design, and apply rigorous data science methods. Serve as the front-line support for data-related questions from end-users, and be responsible for standardization, documentation, and maintaining a repertoire of answers and solutions to common problems.

Learn more about the great benefits of working for University of Utah: benefits.utah.edu

The department may choose to hire at any of the below job levels and associated pay rates based on their business need and budget.

Design, build, implement, and maintain data processing pipelines for the extraction, transformation, and loading (ETL) of data from a variety of data sources. Develop robust and scalable solutions that transform data into a useful format for analysis, enhance data flow, and enable end users to consume and analyze data faster and easier. Write complex SQL queries to support analytics needs. Evaluate and recommend tools and technologies for data infrastructure and processing.

Collaborate with engineers, data scientists, data analysts, product teams, and other stakeholders to translate business requirements to technical specifications and coded data pipelines. Work with tools, languages, data processing frameworks, and databases such as R, Python, SQL, Mongo

DB, Redis, Hadoop, Spark, Hive, Scala, Big Table, Cassandra, Presto, Strom. Work with structured and unstructured data from a variety of data stores, such as data lakes, relational database management systems, and/or data warehouses. Considered highly skilled and proficient in discipline. Conducts complex, important work under minimal supervision and with wide latitude for independent judgment.

Requires a bachelor’s (or equivalency) + 6 years or a master’s (or equivalency) + 4 years of directly related work experience.

This is a Career-Level position in the General Professional track.

EQUIVALENCY STATEMENT: 1 year of higher education can be substituted for 1 year of directly related work experience (Example: bachelor’s degree = 4 years of directly related work experience).

Data Engineer, III: Requires a bachelor’s (or equivalency) + 6 years or a master’s (or equivalency) + 4 years of directly related work experience.

• Master’s degree in biomedical informatics, computer science, information systems, bioengineering or equivalent, with an emphasis on healthcare.
• 4+ years of experience with healthcare data warehousing, electronic health records (ideally, Epic), and data preparation & analysis.
• Knowledge and experience in applying controlled medical terminologies like SNOMEDCT, LOINC, RxNorm, etc. in healthcare.
• Demonstrated expertise in a broad array of data science theories and techniques.

The University of Utah values candidates who have experience working in settings with students from diverse backgrounds and possess a strong commitment to improving access to higher education for historically underrepresented students.

Individuals…