Senior Product Manager

Senior Product Manager Skip to main content#Senior Product Manager page is loaded## Senior Product Manager Apply locations:
Findlay, Ohio:
San Antonio, Texastime type:
Full time posted on:
Posted Todayjob requisition :
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** An exciting career awaits you
** At MPC, we’re committed to being a great place to work – one that welcomes new ideas, encourages diverse perspectives, develops our people, and fosters a collaborative team environment.# Position Summary Analytics & Innovation is on a mission to create trusted and reusable data products that will connect our value chains and support our strategic commitments. Our vision of data product strategy moves us to a full value chain mindset across data products where these trusted data assets support the integrated value chains.

This is an exciting and challenging time, and we need an experienced Product Manager to join our Data Product Management team.

Our Data Product Managers play a key role in defining and delivering enterprise data products that enable business decision-making, operational optimization, and advanced analytics, As a Data Product Manager, you are responsible for data product discovery and design in partnership with our Digital Partners and business stakeholders for an assigned enterprise domain (Commercial, Midstream, Refining, or Corporate functions).The position requires a strong blend of product management, data strategy, and business domain expertise, with accountability for translating business problems into scalable, high-quality data products (e.g., curated datasets, data models, analytics-ready assets, and AI/ML enablement).

You will partner closely with A&I Product Teams (Data Discovery, Data Integration, Data Science, Data Governance, and Business Intelligence) to deliver reusable and well-architected data products that drive measurable business value.

This position belongs to a family of jobs with increasing responsibility, competency, and skill level. Actual position title and pay grade will be based on the selected candidate’s experience and qualifications.#

Key Responsibilities
* Define and own the strategy, vision, and roadmap for data products, ensuring alignment with business outcomes and enterprise data strategy.
* Translate business capabilities, KPIs, and decision needs into data product requirements and measurable value outcomes.
* Partner with Data Partner, Digital Partners, and business stakeholders to ensure data products are aligned to cross-functional processes and “run-as-one” priorities.
* Conducts or facilitates customer research, product discovery, and synthesizes market factors into a cohesive product strategy.
* Collaborates with internal customers to understand challenges and opportunities.
* Collects quantitative data and takes a data driven approach to evaluate the viability of product initiatives.
* Lead data product discovery efforts, including identification of required data sources, data domains, and transformation needs.
* Define data product scope, including data models, business rules, semantic layers, and consumption patterns (e.g., dashboards, APIs, AI use cases).
* Ensure data products are designed for reusability, scalability, and interoperability across business units.
* Ensure data products adhere to enterprise data governance, quality, security, and compliance standards.
* Partner with Data Engineering and Architecture teams to define data lineage, metadata, and stewardship expectations.
* Partner with Data Governance to incorporate data quality metrics, monitoring, and observability into product definition and backlog.
* Act as the primary bridge between business stakeholders and technical delivery teams for data-centric products.
* Collaborate with Data Engineers, Data Scientists, Architects, and UX/BI teams to align on data design, usability, and technical feasibility.
* Drive alignment across work streams to ensure consistent definitions and shared data assets across domains.
* Translate product strategy into well-defined epics and features specific to data pipelines, transformations, and consumption layers.
* Prioritize backlog items based on business value, data readiness, dependencies, and…