Principal Product Manager, Core Data Systems

Ford Ford · Auto · Boston, MA +1 · Enterprise Technology

The Principal Product Manager will lead the strategy and delivery of data products for Ford's manufacturing technology, including robotics, automation, and vision systems. This role focuses on ensuring data is captured, governed, and delivered securely and reliably to power manufacturing systems and enable analytics and ML teams. The position involves defining product roadmaps, building data products like telemetry and vision datasets, and driving standardization across systems.

What you'd actually do

  1. Define the vision and roadmap for ATP’s core data systems products, aligned to business outcomes and platform scalability.
  2. Build and evolve data products such as: - Robotics telemetry and event datasets (health, faults, tasks, utilization) - Fleet and site performance datasets and metrics layers - Vision datasets (images/video) with metadata, labeling workflows, and training-ready packaging - APIs and curated datasets that enable analytics and ML teams to move faster - Contextualization of data from the shopfloor and analytics.
  3. Partner with engineering, data science, and operations to define requirements for data quality, latency, reliability, and cost—especially for high-volume image/video data.
  4. Drive standardization across systems and suppliers by defining schemas and data contracts that work across sites and robotics platforms.
  5. Establish a clear approach to data access and governance across OT and IT environments (security, privacy, retention, auditability).

Skills

Required

  • 10+ years of experience in product management and/or building data products at scale.
  • Track record delivering data products or platform capabilities used by multiple teams (not one-off dashboards).
  • Strong understanding of data product fundamentals: event data, batch vs streaming, data modeling, metadata/lineage, and data quality/observability.
  • Ability to translate complex, ambiguous problems into clear priorities, requirements, and measurable outcomes.
  • Strong communication and stakeholder leadership skills, including comfort working with both executives and technical teams.

Nice to have

  • Master’s degree or MBA.
  • Experience with robotics, automation, or industrial telemetry data (uptime, MTTR, utilization, task success).
  • Experience building products for vision/ML data (image/video pipelines, labeling workflows, dataset quality and versioning).
  • Experience bridging OT and IT environments, including edge constraints and secure data movement.
  • Familiarity with governance and security patterns (RBAC/ABAC, encryption, retention, audit controls) in enterprise settings.
  • Experience enabling ML teams through well-designed data interfaces, training data practices, or MLOps-adjacent workflows.

What the JD emphasized

  • data products at scale
  • data products or platform capabilities used by multiple teams
  • high-volume image/video data

Other signals

  • data products
  • manufacturing technology
  • robotics
  • vision systems
  • ML teams