Hybrid Data Engineer, Athletics presso University of Pittsburgh

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.

Required Technical Experience:

• 3+ years data engineering experience developing data pipelines

• Proficiency in Python, SQL & Pyspark for data manipulation & backend development

• Experience managing databases/warehouses (Iceberg & Snowflake preferred) &

   building batch or streaming data pipelines using cloud-based data services 

• Experience with Terraform for IaC & GitHub for version control.

• Experience facilitating ML Ops.

• Prior experience in the sports industry in a technical role.

Required Non-Technical Experience:  Strong collaboration skills with demonstrated ability to work well in a team; Self-directed & motivated in fast-paced environment.

Desired (but not Mandatory):  Experience working with raw sports tracking data; Experience developing full stack applications & serverless backend architectures.

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Evaluates business requirements, creates advanced data ingestion processes and modeling, and provides extensive support for databases and relevant services. Designs new data architectures. Ensures data quality and delivery. Trains and assists lower-level data engineers; often serves as team lead. Supports data analysts and scientists with expert-level research and consulting.

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Generally sedentary desk work with computer-keyboard-video phone other than occasional travel for campus meetings/events or conferences, etc.  Must be able to sit or stand for prolonged periods of time.

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