Senior Product Manager, Data Platform

By bringing together next-gen technology and the finest live data available, Genius Sports is enabling a new era of sports for fans worldwide, delivering experiences that are more immersive, interactive and personalized than ever before. Learn more at geniussports.com. The Role - Senior Product Manager We are seeking a Senior Product Manager to join our Data AI team and lead product strategy for the platform capabilities that power the ingress, transformation, storage, and egress of highly granular, live sports data. The ideal candidate combines strong product instincts with deep platform thinking and technical fluency in real-time data systems. You should be equally comfortable defining long-term strategy, rationalizing legacy tooling, partnering with engineers on highly scalable data platforms, and enabling downstream analytics, AI, and API products. Responsibilities: This role sits at the center of our sports data ecosystem. You will work across Sports Tech, Data Collection, Engineering, BI, Data Science, Betting, Fan Engagement, Advertising, and commercial stakeholders to build the shared tools and platforms that capture, process, analyze, and distribute real-time team- and player-level sports data at scale. You will play a key role in one or more of the following areas: Maintain and Modernize Data Pipelines Identify, assess, and prioritize new data sources for onboarding, including fixtures data, odds data, player and match data, product usage data, customer data, and other relevant internal and external datasets. Partner with data owners and engineering teams to understand available attributes, business value, integration methods, and operational considerations for each source. Work with engineering to define, build, and evolve a robust, real-time data platform capable of ingesting, aggregating, transforming, and exposing terabytes of sports, betting, customer, and product intelligence data. Partner with engineering to design and implement scalable data cleaning, normalization, and transformation processes that improve data consistency, usability, and compliance. Drive requirements for end-to-end monitoring, alerting, observability, and reporting to ensure highly available, low-latency, and performant data processing across the platform. Ensure ETL design, schema management, storage, and retention practices align with internal best practices as well as security and privacy standards. Enable Data Warehousing, Reporting, and Advanced Analytics Work closely with stakeholders across marketing, business intelligence, customer intelligence, product planning, and other functions to understand business needs and make data accessible for analysis and decision-making. Partner with BI and analytics teams to deliver self-serve reporting capabilities, including dashboards, semantic layers, cubes, and other tools that broaden access to customer and product intelligence. Support the evaluation and integration of advanced analytical tools and data workflows that enable data scientists and analysts to model customer behavior, generate predictive insights, and inform betting and personalized fan engagement use cases. Help define the data foundations needed to support AI and machine learning use cases across the business. Build, Maintain, and Evolve Data Distribution Tools Partner with stakeholders across sports betting, fan engagement, advertising, leagues, and teams to understand their data consumption needs and deliver scalable distribution capabilities. Own the API and data distribution product strategy and roadmap, ensuring alignment with key internal and external stakeholders. Define and prioritize user stories and backlog items related to data sharing, API access, entitlements, delivery mechanisms, and partner integrations. Support the development of push- and pull-based distribution patterns that make data available reliably and efficiently across a range of products and customers. Partner with Advertising a ... (truncated, view full listing at source)