Associate Data Platform Engineer

Madison Square Garden Entertainment Corp. (MSG Entertainment) is a leader in live entertainment, delivering unforgettable experiences while forging deep connections with diverse and passionate audiences. The Company’s portfolio includes a collection of world-renowned venues – New York’s Madison Square Garden, Infosys Theater at Madison Square Garden, Radio City Music Hall, and Beacon Theatre; and The Chicago Theatre – that showcase a broad array of sporting events, concerts, family shows, and special events for millions of guests annually. In addition, the Company features the original production, the Christmas Spectacular Starring the Radio City Rockettes, which has been a holiday tradition for more than 90 years. More information is available at www.msgentertainment.com.
Who are we hiring?
The Associate Data Platform Engineer will be responsible for supporting, enhancing, and maintaining Madison Square Garden Company’s advanced data platforms used for both analytics and for the integration of business and customer-facing applications. The Associate Data Platform Engineer will have the opportunity to work with data that spans all of MSG’s business units and includes metrics for the Knicks, Rangers, Rockettes, and concerts held in The Madison Square Garden Company’s iconic venues. The Associate Data Platform Engineer will work closely with both Data Platform Engineers and Sr Data Platform Engineers supporting the development of solutions that establish MSG as a leader in the use of data to drive outstanding business performance by making actionable insights available when and where they add the most value
What will you do?
Support, maintain, and optimize components of the Madison Square Garden enterprise data architecture that power analytics and production reporting across the business, working hands-on with Python, SQL, Amazon Redshift, and Amazon Athena.
Partner with business stakeholders and Business Intelligence developers to analyze complex business questions and deliver clear, data-driven answers.
Develop and maintain enhancements to the enterprise data warehouse, ensuring new data sources and business requirements are integrated reliably and at scale.
Build, maintain, and extend ETL transformation processes that populate dimensional data models, applying version control, modular SQL design, and testing practices to keep the analytics layer maintainable, well documented, and trusted for reporting across the organization.
Implement data quality checks and validation logic throughout the pipeline lifecycle, proactively identifying anomalies, reconciliation gaps, and upstream source issues before they reach business users.
Develop and schedule workflows using modern orchestration tooling such as Apache Airflow, with attention to dependency management, retry logic, and monitoring.
Triage, troubleshoot, and resolve issues across data solutions, working with technical and business partners to identify root causes and implement durable fixes.