Data Product Manager, Curation

Rush Street Interactive (NYSE: RSI) is a market leader in online casino and sports betting, currently operating real-money gaming with our brands: BetRivers.com, PlaySugarHouse.com, and RushBet.co. We’re building bridges between online, social and land-based gaming businesses to create amazing, integrated experiences that keep players in the game. The Data Product Manager – Curation is responsible for designing and managing curated data products that power reporting, analytics, and emerging advanced analytics use cases across RSI like Machine Learning. This role focuses on building trusted, well-modeled, and well-documented data layers that translate raw source data into reusable, business-aligned datasets. The position partners closely with analytics and analyst teams as well as data and analytics engineering to improve data consistency, usability, and self‑service adoption. While machine learning and advanced analytics are longer‑term areas of evolution, this role lays the semantic and structural foundation required to support them in the future. This role is critical to closing the gap between ingestion and insight and strengthening RSI’s enterprise data maturity. What You’ll Do Design and manage curated data products composed of fact and dimension tables optimized for reporting, analytics, and downstream analytical use cases. Develop and maintain semantic and subject‑area data models that support analytics self‑service and consistent business definitions. Partner with analytics and BI teams to understand reporting needs and translate them into scalable, reusable curated datasets. Lead schema design, join logic, and standardization efforts to improve trust, consistency, and cross‑domain usability of data. Collaborate with data engineering teams on data transformations, modeling standards, and performance optimization. Support future advanced analytics and ML use cases by ensuring curated datasets are well‑structured, well‑documented, and extensible. Establish governance standards for curated datasets, including documentation, lineage, naming conventions, and data quality monitoring. Track adoption and usage of curated data products, incorporating stakeholder feedback to iteratively improve models and definitions. What You’ll Bring Bachelor’s degree in Information Systems, Data Science, Computer Science, or a related field, preferred, or equivalent experience. 5+ years of experience in data product, analytics infrastructure, or data modeling roles. Stakeholder Management: 5+ years of experience partnering with BI, analytics, and business stakeholders to gather requirements and deliver trusted data products. Analytics & Product Thinking: Strong understanding of how curated data enables reporting, self‑service analytics, and consistent decision‑making. Data Modeling: 3+ years of experience designing dimensional models, schemas, and semantic layers for analytics or reporting use cases. ML Awareness (Foundational): General familiarity with how curated data may support future ML or advanced analytics use cases (e.g., feature readiness, aggregation strategies), without expectation of hands‑on model development. Technical Proficiency: Advanced SQL skills and hands‑on experience working with data marts, transformations, and analytical datasets. Documentation & Governance: Experience maintaining semantic definitions, data catalogs, and quality standards to ensure data is discoverable, explainable, and trustworthy. Able to travel occasionally both domestically and internationally. Pay Range: $100,000 - $140,000 USD Location Eligibility: Open to candidates across the U.S. Rush Street Interactive is an equal opportunity employer and committed to a diverse and inclusive workplace. All qualified applicants will be considered for employment without regard to race, national origin, ancestry, sex, sexual orientation, sexual identity and expression, marital status, family status, lifestyle, age, culture, religion, military and veteran status, citizenship, or disability. #J-18808-Ljbffr Rush Street Interactive