Data Engineer, Athletics

Pitt IT Analytics

Who We Are: Panthers Data and Analytics represents the University of Pittsburgh Athletics Department as a part of the University’s Pitt IT Analytics team. Our mission is to “Improve decision-making by managing data from source to strategy.” We help the Athletics Department improve across four domains areas: administration, revenue generation, sports science, and sports analytics.

Who we are looking for: The Data Engineer, Athletics will be the primary individual contributor to data engineering efforts within Panthers Data and Analytics. You bring expertise, energy, and enthusiasm to help our program in the critical work of data infrastructure management, data pipeline development, data modeling, and more using an AWS-centered cloud environment.

Who you will work with: The Pitt IT Analytics team is a cross-functional team with hybrid work structure (some on-site and some remote staff). The position will regularly collaborate with other members of the Pitt IT Analytics team including data engineers, analytics engineers, and data scientists.

Essential Functions

What you will work on: The position will work on projects across all domains. Projects could include data related to transactions, customers, marketing, roster management, sports performance, among other subjects. You will manage our data infrastructure, help curate data as an asset, and help the team leverage our data for insights. Most of your time will be on individual code contributions, but you will also be responsible for driving architectural design discussions and collaborating on best practices.

Develop data pipelines: Design, build, and maintain robust and efficient data pipelines and APIs that collect, process, and integrate data from various sources. Curate data for data science and analytics: Curate, organize, and optimize data in data warehouses and lakes to ensure it is accurate, accessible, and ready for various data science and analytics use cases. Enhance and expand the data platform: Implement scalable solutions that improve and extend the utility of our data infrastructure and platform(s). Facilitate AI/ML operations: Partner with Data Scientists to operationalize machine learning and artificial intelligence models. This may include model deployment and leveraging LLMs through agentic workflows. Document engineering work : Document and share details on engineering standards, practices, and workflows. Special projects and other duties as assigned.

Required Documents

Resume

Optional Documents

Cover Letter