Jack Radlinger
About Jack Radlinger
Jack Radlinger is a Software Developer at Boston Scientific in St. Paul, Minnesota, specializing in data ingestion and SQL Server performance.
Title
Jack Radlinger holds the position of Software Developer at Boston Scientific. He assumed this role in 2021, and he operates out of St. Paul, Minnesota, United States.
Professional Experience at Boston Scientific
Jack Radlinger has an extensive history with Boston Scientific, where he currently serves as a Software Developer. Prior to his current role, he worked as a Rotational Associate from 2019 to 2021, and as an IT Intern from 2018 to 2019. In his current and previous roles at Boston Scientific, Jack contributed significantly to various technology-driven initiatives in the Greater Minneapolis-St. Paul Area.
Education and Expertise
Jack Radlinger attended the University of Minnesota - Carlson School of Management, achieving a Bachelor's degree in Management Information Systems. His expertise includes developing and optimizing stored procedures for data ingestion and transformations in Manufacturing Analytics Data Warehouses. Additionally, he has specialized skills in ingesting data from various source systems into SQL Server with near real-time performance.
Past Employment
Jack Radlinger's career includes diverse roles. He worked as a Crew Member at Trader Joe's in the Madison, Wisconsin Area for three months in 2016. He also served as a Line Worker at Cardinal Glass Industries in Spring Green, Wisconsin from 2015 to 2017. These roles preceded his time at Boston Scientific and his academic endeavors at the University of Minnesota.
Database Development and Deployment
Jack Radlinger has demonstrated significant capabilities in database development and deployment. He developed and optimized stored procedures that facilitate data ingestion and transformation within a Manufacturing Analytics Data Warehouse. Moreover, he has been responsible for testing and deploying new database features globally, overseeing more than 16 instances. His work ensures near real-time performance for data ingestion, achieving completion in under one minute.