Senior Data Engineer - ETL, Pipelines & SQL

University of Utah; Campus (IL); On-site; USD 90,000 - 120,000; Full time

Job summary

The University of Utah is seeking a Data Engineer IV to design, build, implement, and maintain ETL pipelines that ingest data from diverse sources and transform it for analytics. You will write complex SQL queries, evaluate data tools and technologies, and collaborate with engineers, data scientists and product teams to translate requirements into robust data solutions.

This advanced-level role in the General Professional track involves working with R, Python, SQL, MongoDB, Hadoop, Spark, Hive,

Qualifications

• Requires a bachelor’s (or equivalency) + 8 years or a master’s (or equivalency) + 6 years of directly related work experience.
• This is an Advanced-Level position in the General Professional track.
• Data Engineer IV level eligible depending on business need and budget.

Responsibilities

• Design, build, implement, and maintain data processing pipelines for ETL from various sources.
• Develop robust and scalable solutions that enable analysis and faster data consumption.
• Write complex SQL queries to support analytics needs and evaluate tools/technologies for data infrastructure.
• Collaborate with engineers, data scientists, data analysts, product teams, and other stakeholders to translate requirements into data pipelines.
• Work with data processing frameworks and databases such as R, Python, SQL, MongoDB, Redis, Hadoop, Spark, Hive, Scala, BigTable, Cassandra, Presto, Storm.

Skills

SQL querying

Data analysis

Cross-functional collaboration

Education

Bachelor’s degree or equivalent

Master’s degree or equivalent

Tools

R

Python

SQL

MongoDB

Redis

Hadoop

Spark

Hive

Scala

BigTable

Cassandra

Presto

Storm

Job description

The University of Utah is seeking a Data Engineer IV to design, build, implement, and maintain ETL pipelines that ingest data from diverse sources and transform it for analytics. You will write complex SQL queries, evaluate data tools and technologies, and collaborate with engineers, data scientists and product teams to translate requirements into robust data solutions.

This advanced-level role in the General Professional track involves working with R, Python, SQL, MongoDB, Hadoop, Spark, Hive,