Manager, Product Owner – Data Curation

CME Group•Chicago, IL

About The Position

The Manager, Product Owner for Data Curation serves as the primary liaison between technical data engineering teams (PODs) and strategic business stakeholders—including internal data analytics, reporting, and the CME Data Commercialization division. Responsible for maximizing value delivery within the Unified Data Platform (UDAP) data lakehouse, this role defines, maintains, and prioritizes the product backlog (user stories, enablers, and technical debt). By leveraging familiarity with CME Group’s exchange datasets, establishing a clear product vision, defining acceptance criteria, and enforcing data governance standards, the Product Owner ensures the delivery of fit-for-purpose, high-quality curated data assets aligned with client demand and strategic goals.

Requirements

Bachelor’s degree required (Business, Computer Science, Data Science, Product Management, or related field).
3+ years of experience as a Product Owner, Technical Product Manager, or Data Manager within modern enterprise data platform environments (Snowflake, Databricks, BigQuery, AWS, Azure, etc.).
Strong understanding of Agile methodologies. Experience operating within a SAFe environment is highly preferred (SAFe POPM or CSPO certifications are a strong plus).
Proficient in querying data (e.g., SQL basics) to validate assumptions, investigate issues, and drive data-informed decisions.
Deep understanding of the complete trade lifecycle and financial derivatives (futures, options), including market liquidity, order book mechanics, post-trade processing, clearing workflows, and risk management inputs.

Nice To Haves

Hands-on knowledge and familiarity with CME Group's Exchange Data sets (e.g., product reference, market/tick data, post-trade, order book, settlement data, and market data feeds).
Hands-on experience or working familiarity with modern data lakehouse architectures (e.g., BigQuery, Snowflake) enterprise data warehousing concepts, and Business Intelligence (BI) visualization tools (e.g., Looker, Tableau, Power BI).
Exceptional ability to bridge the gap between technical engineering teams and business stakeholders, seamlessly translating complex data architecture into clear business value, and converting commercial goals into actionable technical requirements.
Direct experience working alongside business stakeholders, applied analytics, data science, or external data product delivery teams.

Responsibilities

Define & Execute Vision: Translate the overall data curation strategy into a cohesive, prioritized product backlog that accelerates business value across analytics, reporting, and external commercial solutions.
Stakeholder Alignment: Collaborate directly with key enterprise stakeholders to obtain requirements, and prioritize features balancing between real-time client demand and enterprise objectives
Data Prototyping & Product Conceptualization: Advanced proficiency in querying datasets (e.g., BigQuery SQL) to perform hands-on exploration and prototyping against datasets. Build small-scale data proofs-of-concept (POCs) to conceptualize data products, validate business assumptions, and communicate requirements clearly to engineering teams and technical leads.
Adoption & Domain Ownership: Drive enterprise-wide adoption of the data lakehouse, fostering a culture of responsible data domain ownership and consistent platform utilization.
Agile Ceremonies: Lead core Agile ceremonies for your Pod, including Sprint Planning, Backlog Refinement, Sprint Reviews, and Retrospectives.
PI Planning: Participate actively in Program Increment (PI) Planning, drafting team PI objectives and identifying cross-pod dependencies within the Agile Release Train.
Standards Advisory Partner: Serve as a strategic advisory partner across business units to uphold data lakehouse platform standards and improve enterprise-grade data management practices.
Quality & Metadata Excellence: Ensure curated data assets meet consumer-desired quality, usability, and experience standards by enforcing robust metadata management
Process Automation: Spearhead the implementation of scalable, reusable, and automated data validation processes to continuously verify curated data assets against trusted source systems.