Manager, Data Product Management

Ford•Dearborn, MI

1d•$141,700 - $268,300•Onsite

About The Position

The Manager, Data Product Management for Ford’s Enterprise Data Platform owns the strategy, quality, and business value of data in Ford’s Enterprise Data Lake. The lake brings together company line-of-business and third-party data, architected and curated for Analytics, AI, Reporting, and Operational Data Store (ODS) use cases. The role focuses on ensuring data is trusted, discoverable, well-governed, and expressed in business language. The manager leads six Supervisors who are each accountable for defining, designing, building, and managing a Domain Data Hub. Each hub delivers curated collections of data products that describe business concepts such as Customer, Vehicle, Dealer, Part, and Order. The role requires data product management expertise, understanding of data modeling and governance, people leadership, and the ability to engage senior enterprise stakeholders. The position develops the data product vision and roadmap, establishes enterprise standards and frameworks, and measures portfolio outcomes such as adoption, reuse, time-to-data, business impact, and retirement of redundant or low-value assets. It oversees the lifecycle and consistent practices of domain hubs, resolves cross-hub dependencies and overlapping definitions, and manages portfolio resources and priorities. The manager oversees the development of business concepts, semantic definitions, shared glossary content, and fit-for-use products for Analytics, AI/ML, Reporting, and ODS. The role partners with data producers and Data Architecture on sourcing, modeling, integration, quality, timeliness, master and reference data, and lineage. It also ensures data products are documented and governed appropriately for AI and generative AI use. The position owns data quality across domain hubs and partners with Governance, Privacy, and Security teams on classification, protection, and regulatory compliance. It establishes ownership and stewardship, metadata and catalog documentation, and data lifecycle policies. The manager engages business stakeholders and data users to discover needs, communicate progress and outcomes to senior leadership, and coordinate among business, producers, consumers, and platform teams. The role partners with the Enterprise Data Platform Product Manager and platform teams on requirements and roadmap input; the platform itself is owned by others. It drives data product adoption through onboarding, training, documentation, and enterprise catalog promotion, analyzes usage and feedback, manages portfolio costs, and fosters continuous improvement, experimentation, and data literacy. Relocation assistance and sponsorship are available. This is leadership level 5, with a stated salary range of $141,700–$268,300. Final salary grade and base pay depend on the candidate’s skills and experience, job scope, responsibility, and competitive market value. Candidates must be legally authorized to work in the United States; employment eligibility verification is required at hire.

Requirements

Bachelor’s degree in Computer Science, Engineering, Data Science, Information Systems, Statistics, Applied Mathematics, Business Analytics, or a related field.
At least 8 years of experience in data management, data engineering, analytics, or product management.
At least 3 years focused on product management, with a track record of delivering enterprise-scale data solutions.
At least 3 years of people leadership experience, including managing managers or supervisors or leading large, multi-team organizations.
Strong understanding of data modeling, data architecture, data lakes or lakehouses, master and reference data, metadata, and lineage.
Hands-on familiarity with cloud data environments such as GCP, AWS, or Azure.
Experience with enterprise data governance, data quality, and data privacy and security.
Experience defining and delivering data products or data-as-a-product approaches, including data contracts, service levels, and product metrics.
Ability to define and execute product roadmaps and manage complex, cross-functional programs in a fast-paced environment.
Excellent communication and stakeholder management skills, including influencing senior leaders and explaining technical concepts in business language.
Legal authorization to work in the United States; employment eligibility verification is required at hire.

Nice To Haves

An advanced degree.
Experience in the automotive or manufacturing industry.
Familiarity with semantic layers, business glossaries, and data catalog tools.
Exposure to AI/ML and generative AI data requirements.
Experience with data visualization and analytics tools.
Experience within Google Cloud Platform.
Experience with Agile/Scrum methodologies, including Jira.

Responsibilities

Develop and communicate the data product vision for the Enterprise Data environment and domain data hubs, aligned with Ford’s data, AI, and digital transformation goals.
Define and drive the data product roadmap, prioritizing domains, business concepts, and data products using business value, customer feedback, data-driven insights, and enterprise priorities; partner with non-direct-reporting data hub owners.
Establish and manage the enterprise data product framework, including standards for data products, business concepts, and domain data hubs and their relationships.
Define and track portfolio value and outcomes, including adoption, reuse, time-to-data, business impact, and retirement of redundant or low-value data assets.
Lead, coach, and develop six Supervisors responsible for the end-to-end lifecycle of domain data hubs; set objectives, accountabilities, and performance expectations.
Establish consistent practices across hubs for design patterns, naming and modeling conventions, definition of done, release processes, and support while accommodating domain needs.
Manage cross-hub dependencies and shared concepts, resolving overlaps, conflicting definitions, and duplicate data to create consistent enterprise views.
Allocate resources and manage the portfolio across hubs, balancing capacity, skills, and priorities while developing talent and a culture of data product ownership.
Oversee design and delivery of business concepts in business language, supported by a shared business glossary, semantic definitions, and consistent metrics.
Ensure data products are fit for Analytics, AI/ML, Reporting, and ODS use, with defined owners, schemas, service levels, and data contracts.
Partner with source-system owners and data producers to source appropriate data and agree on quality and timeliness expectations.
Partner with Data Architecture on modeling and integration standards for structured, unstructured, batch, and real-time data, including master and reference data alignment and source-to-consumption lineage.
Ensure data readiness for AI by providing high-quality, documented, appropriately governed products for training, grounding, and operating AI/ML and generative AI solutions.
Own data quality for domain data hubs by defining quality rules, measures, and thresholds, monitoring them, and driving remediation at the source.
Partner with Data Governance, Privacy, and Security teams to ensure data classification, protection, and access comply with applicable regulations and Ford policy.
Establish data ownership and stewardship for each business concept and product, including metadata, lineage, and catalog documentation.
Define and manage data lifecycle policies, including retention, archival, and decommissioning.
Collaborate with business units and other stakeholders to understand data needs and translate them into data products and business concepts.
Conduct customer discovery through interviews, surveys, and regular pulse checks to identify needs, pain points, and satisfaction levels.
Manage senior leadership relationships and provide product reviews on progress, outcomes, risks, and opportunities.
Serve as liaison among business stakeholders, data producers, data consumers, and platform teams to align goals and communication.
Partner with the Enterprise Data Platform Product Manager and platform teams to communicate data-driven requirements and ensure platform capabilities support data products; provide input to the platform roadmap.
Drive adoption and reuse through onboarding, training, documentation, best-practice guides, education, evangelism, and enterprise catalog promotion.
Analyze usage data and user feedback to continuously improve data product quality, usability, and value.
Manage the data portfolio budget with Finance and Procurement, optimizing storage, duplication, and consumption costs while delivering valuable products.
Stay informed about data product management, data mesh and fabric hybrid models, data-as-a-product approaches, semantic modeling, governance, and AI.
Foster continuous improvement, experimentation, and data literacy within the team and across the enterprise.

Benefits

Immediate medical, dental, vision, and prescription drug coverage.
Flexible family care days, paid parental leave, new-parent ramp-up programs, and subsidized backup child care.
Family-building benefits, including adoption and surrogacy expense reimbursement and fertility treatments.
Vehicle discount program for employees and family members, and management leases.
Tuition assistance.
Employee resource groups.
Paid time off for individual and team community service.
Paid holidays, including the week between Christmas and New Year’s Day.
Paid time off and the option to purchase additional vacation time.
Relocation assistance is available.
Sponsorship is available.