Senior Data Scientist / ML Engineer

Ford Motor Company

. Design and evolve Ford’s data mesh architecture across manufacturing and enterprise domains .

Posted 9/22/2026full-timeRedford • Michigan • United StatesSenior💰 $132,800 - $250,800 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Expertise in data architecture and engineering, with a strong focus on GCP technologies and data governance practices. Proven ability to lead technical teams and drive the development of high-quality data products in manufacturing and enterprise environments.

Highest-signal resume keywords

Data ArchitectureGCP TechnologiesData GovernanceData ModelingStakeholder Management

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Hard Skills

Data EngineeringDatabase DesignData WarehousingSQLPythonData Modeling ToolsData Mesh ArchitectureAI/ML CapabilitiesData Quality ManagementData Product Development

Soft Skills

LeadershipMentoringCollaborationCommunicationStakeholder Management

Tools & Technologies

GCPBigQueryCloud StorageDataformData FusionAstronomerData Pipeline ToolsMetadata Management SolutionsData Catalog SolutionsObservability Tools

Industry Keywords

Manufacturing DataEnterprise DataComputational GovernanceData Product ContractsInteroperability StandardsPrivacy ComplianceData Quality SLAsSemantic LayersKnowledge GraphsOntologies

Tech Stack

Tools & technologies

BigQueryCloudCyber SecurityGoogle Cloud PlatformPythonSQL

About the role

Key responsibilities & impact

Design and evolve Ford’s data mesh architecture across manufacturing and enterprise domains
Define domain boundaries, data product contracts, and interoperability standards
Establish and maintain federated computational governance policies
Champion adoption of GCP, Vertex AI, and agentic AI/LLM orchestration
Lead transformation of raw manufacturing-system data into curated, documented, high-quality data products
Define and enforce data product ownership, schema versioning, quality SLAs, discoverability, and access controls
Oversee batch and streaming ingestion, transformation, and publishing pipelines
Design data structures and semantic layers, including ontologies and knowledge graphs, for AI agents
Design and develop enterprise, conceptual, logical, and physical data models
Partner with product and analytics teams on data requirements, architecture guidance, models, and design reviews
Establish architecture principles covering catalog, lineage, observability, security, and interoperability
Drive data quality profiling, metrics, monitoring, reporting, and remediation
Drive adoption of GCP as the technical backbone of the data mesh and data product ecosystem
Evaluate and implement metadata management and data catalog solutions
Establish monitoring, observability, and SLA tracking for published data products
Own and evolve the federated governance framework
Implement automated policy enforcement for schema validation, access control, metadata cataloging, and lineage tracking
Partner with cybersecurity, legal, and compliance teams to classify and protect sensitive data
Ensure privacy and compliance by design

Requirements

What you’ll need

Master’s degree in computer science, Information Systems, Data Engineering, or a related field, or equivalent combination of relevant education and experience
5+ years of experience in data architecture, data engineering, or advanced database design/modeling, including designing or implementing databases, data warehouses, or data marts, with exposure to large-scale manufacturing or industrial data environments
15+ years of experience leading, managing, or mentoring technical teams
Hands-on experience creating data models using data modeling tools
Deep, hands-on experience with GCP technologies including BigQuery, Cloud Storage, Dataform, Data Fusion, Astronomer, or similar cloud data engineering tools
Demonstrated experience designing or implementing data mesh or domain-oriented data architectures
Understanding of AI/ML capabilities, with experience modeling semantic layers, knowledge graphs, or ontologies for a data platform
Knowledge of data governance, data quality, and data product marketplace enablement practices
Proficiency in SQL, Python, and modern data pipeline/orchestration tools
Strong stakeholder management skills, with the ability to work across plant floor operations teams and enterprise IT/analytics functions
Must be legally authorized to work in the United States
Visa sponsorship is not available

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
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
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