Director, Data Engineering, Architecture

Ford Motor Company

Director leading the evolution of Ford's Enterprise Data Platform into an AI-Ready future. Guiding a team of engineers and architects to optimize massive enterprise data management.

Posted 5/21/2026full-timeDearborn • Missouri • 🇺🇸 United StatesLead💰 $141,700 - $268,300 per yearWebsite

Tech Stack

Tools & technologies

BigQueryCloudGoogle Cloud Platform

About the role

Key responsibilities & impact

Define the Vision for AI Readiness: Establish and document the enterprise standards for AI-Ready data, including semantic integrity, automated metadata tagging, high-fidelity pipelines, etc.
Drive Platform Evolution & Modernization: Proactively identify and champion the adoption of next-generation technologies and cloud-native patterns. Act as a strategic catalyst for transitioning the EDP toward higher-maturity operating models, ensuring Ford remains at the cutting edge of data and AI innovation.
Design and Build for Agentic Intelligence: Work cross-functionally within EDP to design and build data for AI agents to interpret without human intervention while ensuring consistency and context across the enterprise.
Collaboration & Leadership: Lead and mentor an organization of Data Architects and Engineers. Working within the Data Platform and Engineering team to ensure solutions are scalable and executable.
Privacy & Compliance by Design: Ensure development patterns enable Ford’s rigorous commitment to data security and global privacy regulations.

Requirements

What you’ll need

Education: Bachelor’s degree in Computer Science, Informatics, Data Engineering, or a related field.
Experience: 12+ years of experience in Cloud-Based Data Architecture, Engineering or a related field, with experience in a leadership role.
People Leader Experience: 3+ years of experience leading technology teams.
GCP Expertise: Deep technical proficiency in the Google Cloud Platform ecosystem, specifically BigQuery, Dataflow, Pub/Sub, and Cloud Storage.
Data Operations Background: Understand CI/CD, and site-reliability engineering principles as they apply to massive data platforms.
AI/ML Foundations: Strong understanding of modern AI requirements, including experience with Vector databases, LLM orchestration frameworks, and building data foundations for RAG-based applications.
Strategic Modeling: Expert-level knowledge of data modeling (Relational, Dimensional, Graph) and the ability to define complex semantic ontologies for large-scale enterprises.
Communication: Ability to translate complex architectural concepts into strategic business value for executive leadership.

Benefits

Comp & perks

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

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Hard Skills & Tools

Cloud-Based Data ArchitectureData EngineeringGoogle Cloud PlatformBigQueryDataflowPub/SubCloud StorageCI/CDsite-reliability engineeringdata modeling

Soft Skills

leadershipmentoringcollaborationcommunicationstrategic thinking