Senior Product Manager

Marathon Petroleum Corporation•Findlay, OH

10d•Onsite

About The Position

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.

Requirements

Bachelor’s Degree in Information Systems, related field or equivalent work experience required.
Product Owner certification or Product Management certification preferred.
5+ years of relevant product manager experience required.
Experience delivering or managing data products, analytics platforms, or data-driven solutions in an enterprise environment.
Strong understanding of data ecosystems, including data warehousing, data lakes, ETL/ELT processes, and modern data architectures.
Proven experience working with cross-functional data and analytics teams, including Data Engineering, Data Science, and BI/Visualization.
Experience defining data requirements, data models, or analytics use cases tied to business outcomes.
Familiarity with data governance, data quality, and metadata management practices.
Experience supporting AI/ML or advanced analytics use cases is preferred.
Energy industry or adjacent industry experience preferred, with understanding of operational and financial data domains.
Agile Methodologies - Agile project management is an iterative approach to delivering a project throughout its life cycle, taking incremental steps towards the completion of a project.
Authentic Communicator - Expresses ideas and information, both verbally and in writing, clearly and credibly. Listens to understand and fosters constructive dialogue.
Backlog Management - A prioritized list of work for the development team that is derived from the roadmap and its requirements. The most important items are shown at the top of the product backlog so the team knows what to deliver first.
Business Acumen - Applies knowledge of MPC’s business, industry and the marketplace to advance the organization’s goals. Makes decisions and recommendations clearly linked to MPC’s strategy.
Decision Making - Ability to know when and what decisions should be made and to make several decisions simultaneously in a fast-paced, rapidly changing environment.
Human-Centered Design - An approach to problem solving, commonly used in design and management frameworks that develops solutions to problems by involving the human perspective in all steps of the problem-solving process.
Industry Product Knowledge - Industry product knowledge refers to a comprehensive understanding of the products and services within a particular industry. It encompasses familiarity with the features, functionalities, applications, and specifications of the products offered by companies operating in that industry. Industry product knowledge is crucial for professionals working in sales, marketing, customer service, product development, and various other roles within a company. It enables individuals to effectively communicate the value propositions of products, address customer inquiries, identify market trends, make informed business decisions, and contribute to the development and improvement of products and services within the industry. This knowledge often requires staying updated with the latest advancements, technologies, and market dynamics within the specific industry domain.
Market Trend Analysis - The ability to analyze data that exhibits an ongoing upward or downward pattern that is not due to seasonality or random noise. Able to analyze trends in detecting patterns that could lead to future quality problems, and in forecasting future demand periods
Marketing - Knowledge of Marketing, the process of planning and executing conception, pricing, promotion and distribution of goods, ideas and services to create exchanges that satisfy individual and organizational goals. Understanding of marketing research, consumer marketing, customer marketing and product marketing.
Product Development - The creation, innovation, enhancement or improvement of an existing product, or developing an entirely new kind of product to satisfy the requirements of its end-users.
Product Lifecycle Management (PLM) - The handling of a good as it moves through the typical stages of its product life: development and introduction, growth, maturity/stability, and decline.
Product Strategies - The process of outlining a company's strategic vision for its product offerings by stating where the products are going, how they will get there and why they will succeed.
Storytelling - The process of communicating information, tailored to a specific audience, with a compelling narrative.
Vendor Management - The process to maintain relationships with key vendors that deliver products, services, and support to the business. Simultaneously, negotiating and managing contracts with key service providers to ensure service levels are set appropriately and met on an ongoing basis.
MINIMUM QUALIFICATIONS: Bachelor’s Degree in Information Technology, related field or equivalent experience.
5+ years of relevant experience

Nice To Haves

Energy industry or adjacent industry experience preferred, with understanding of operational and financial data domains.
Experience supporting AI/ML or advanced analytics use cases is preferred.

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 workstreams 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 technical complexity.
Ensure clarity of requirements related to data sources, transformations, validation rules, and acceptance criteria.
Prioritizes the short-term feature backlog and releases, as well as the long-term product roadmap.
Builds and prioritizes a backlog of Epics and Features to connect strategy to execution; ensures items clearly communicate the customer and stakeholder needs to meet key business objectives and strategies for the product.
Collaborates with portfolio teams, stakeholders, and business representatives to address and resolve issues that arise during product development.
Identifies product-related issues, makes decisions, and continuously analyzes trade-offs to ensure development stays on track toward deliverable commitments.
Drive adoption of data products through clear documentation, stakeholder enablement, and integration into business processes.
Define and track value realization metrics (e.g., usage, decision impact, efficiency gains).
Continuously refine products based on user feedback, data insights, and evolving business priorities.