Major League Soccer (MLS) has built Fan Genome, an advanced 360° fan intelligence platform that unifies demographic, behavioral, and transactional data to deliver hyper-personalization and real-time insights across every fan interaction. We are seeking a hands-on technical leader to own the architecture and evolution of MLS’s next-generation data platform—powering Fan Genome while delivering BI self-service and robust analytics engineering frameworks. This role brings together real-time streaming, distributed compute, open table formats, zero-copy analytics, and enterprise-grade governance to enable advanced analytics and fan engagement at scale.

Responsibilities

• Own the technical architecture and feature delivery of MLS’s next-generation cloud-native Lakehouse platform ensuring scalability, performance, and reliability
• Optimize and enhance existing real-time data pipelines built on Apache Kafka, Amazon Kinesis, and Apache Flink to maintain low-latency ingestion and event-driven processing at scale
• Manage and improve distributed compute workflows leveraging Apache Spark for large-scale batch processing, advanced feature engineering, and ML-adjacent workloads
• Oversee and refine open table format implementations (Apache Hudi, Apache Iceberg) to ensure ACID compliance, schema evolution, and efficient incremental processing