Manager, Data Product Management

Ford Motor Company•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 the 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 use cases. The role focuses on ensuring data is trusted, discoverable, well-governed, and expressed in business language. It leads six Supervisors who are accountable for defining, designing, building, and managing Domain Data Hubs—curated collections of data products that describe business concepts such as Customer, Vehicle, Dealer, Part, and Order. The manager defines the data product vision and roadmap, oversees business-concept and data-product development, and establishes consistent enterprise practices across hubs. The role owns data quality and lifecycle policies, partners with governance, privacy, security, architecture, source-system, and platform teams, and ensures data products meet consumer needs and are ready for AI/ML use. It also manages senior stakeholder relationships, customer discovery, adoption and enablement, portfolio resources and budget, and continuous improvement. The Enterprise Data Platform itself is owned by others; this role provides requirements and input to its roadmap. Ford offers relocation assistance and sponsorship for this role. The position is leadership level 5, with a stated salary range of $141,700–$268,300; final salary depends on candidate skills and experience, job scope, responsibility, and market value. Candidates must be legally authorized to work in the United States, and employment eligibility will be verified 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, including at least 3 years focused on product management and 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/lakehouses, master and reference data, metadata, and lineage.
Hands-on familiarity with cloud data environments such as GCP, AWS, or Azure.
Experience with data governance, data quality, and data privacy and security in an enterprise environment.
Experience defining and delivering data products or data-as-a-product approaches, including data contracts, service levels, and product metrics.
Proven 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 the ability to influence senior leaders and explain technical concepts in business language.
Must be legally authorized to work in the United States; employment eligibility will be verified 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 with Google Cloud Platform.
Experience with Agile/Scrum methodologies, including Jira.

Responsibilities

Develop and articulate the data product vision for the Enterprise Data environment and its domain data hubs, aligning it with Ford’s data, AI, and digital transformation goals.
Define and drive the data product roadmap, prioritizing domains, business concepts, and data products according to business value, customer feedback, data insights, and enterprise priorities; partner with non-direct-reporting data domain hub owners.
Establish and manage the enterprise data product framework, including standards for data products, business concepts, and domain data hubs and how they relate.
Define and track portfolio outcomes, including adoption, reuse, time-to-data, business impact, and retirement of redundant or low-value 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, including design patterns, naming and modeling conventions, definition-of-done, release, and support processes, while accommodating domain needs.
Manage cross-hub dependencies and shared concepts, resolving overlaps, conflicting definitions, and duplicate data to support a consistent enterprise view.
Allocate resources and manage the portfolio across hubs, balancing capacity, skills, and priorities and building a talent pipeline and data product ownership culture.
Oversee business-concept design and delivery using business language, a shared glossary, semantic definitions, and consistent metrics.
Ensure data products are fit for Analytics, AI/ML, Reporting, and ODS consumers, with defined owners, schemas, service levels, and data contracts.
Partner with source-system owners and data producers to ensure appropriate data is sourced, understood, and delivered with agreed quality and timeliness.
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 through high-quality, documented, appropriately governed data products for training, grounding, and operating AI/ML and generative AI solutions.
Own data quality for domain data hubs by defining 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 regulatory requirements and Ford policy.
Establish ownership and stewardship for each business concept and data product, including metadata, lineage, and catalog documentation.
Define and manage data lifecycle policies for retention, archival, and decommissioning.
Collaborate with stakeholders across business units to understand data needs and translate them into data products and business concepts.
Conduct customer discovery through interviews, surveys, and pulse checks to identify needs, pain points, and satisfaction.
Manage senior leadership relationships and provide product reviews covering progress, outcomes, risks, and opportunities.
Act 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-product needs.
Provide input to the platform roadmap based on domain hub and data consumer needs.
Drive adoption and reuse through onboarding, training, documentation, best-practice guides, and promotion through the enterprise catalog.
Analyze usage data and user feedback to improve data-product quality, usability, and value.
Manage the data portfolio budget with finance and procurement, optimizing storage, duplication, and consumption costs while delivering high-value 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

Relocation assistance is available.
Sponsorship is available.
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.