Senior Data Scientist / ML Engineer

Ford Motor Company is hiring a Senior Data Scientist / ML Engineer in Redford, MI (hybrid) to help shape a modern data mesh and data product ecosystem, including federated governance, cloud-native pipelines, and semantic layers that support consistent enterprise data interpretation.

Role Overview

This is a full-time, hybrid leadership role at Level 6. The compensation range is USD 132,800 to 250,800 per year, with final salary grade determination based on candidate skills and experience. Base salary will be set within the applicable range according to job scope, responsibility, and competitive market value. For more information on salary and benefits, see: https://fordcareers.co/LL6.

Location: Redford, MI (hybrid). Visa sponsorship: not available. Relocation assistance: not provided. Employment eligibility must be verified at hire for candidates legally authorized to work in the United States.

Responsibilities

• Design and evolve Ford’s data mesh architecture across manufacturing and enterprise domains, including defining domain boundaries, data product contracts, and interoperability standards.
• Establish and maintain federated computational governance policies (schema standards, data quality SLAs, security classifications, lineage and retention requirements) applied consistently across decentralized domain teams.
• Lead modernization of legacy data workflows by adopting next-generation technologies and cloud-native patterns using GCP, Vertex AI, and agentic AI/LLM orchestration.
• Transform raw data landing in cloud platforms from manufacturing systems into curated, documented, high-quality data products.
• Define and enforce data product standards covering ownership, schema versioning, SLAs for freshness/completeness/accuracy, discoverability, and access controls.
• Oversee ingestion, transformation, and publishing pipelines (batch and streaming) that convert raw operational data into standardized, reusable assets.
• Design and build data structures and semantic layers (ontologies and knowledge graphs) to enable AI agents to interpret enterprise data consistently with minimal human intervention.
• Design and develop data models (enterprise, conceptual, logical, and physical) for assigned domains, and manage models in a shared repository.
• Partner with product and analytics teams to convert use cases into data requirements, providing architecture guidance, data models, and design reviews.
• Establish and enforce data architecture principles and best practices for data products, including catalog, lineage, observability, security, and interoperability.
• Drive data quality initiatives by profiling source-system data, defining quality requirements and metrics, and guiding monitoring, measurement, reporting, and remediation.
• Drive adoption of cloud services such as GCP as the technical backbone for the data mesh and data product ecosystem.
• Evaluate and implement metadata management and data catalog solutions to support discoverability and trust across the mesh.
• Establish monitoring, observability, and SLA tracking for published data products.
• Own and evolve the federated governance framework, balancing global standards with domain-level autonomy to support compliance with Ford’s data security, privacy, and regulatory requirements.
• Implement automated policy enforcement (schema validation, access control, metadata cataloging, lineage tracking) using GCP-native and third-party tooling.
• Partner with cybersecurity, legal, and compliance teams to classify and protect sensitive manufacturing and enterprise data.
• Ensure development patterns support Ford’s data security requirements and global privacy regulations, including privacy and compliance by design.

Requirements

• Master’s degree in computer science, Information Systems, Data Engineering, or a related field, or an 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 (direct people leadership, matrixed leadership, or lead/owner roles directing cross-functional 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, including 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 or orchestration tools.
• Strong stakeholder management skills, including the ability to work across plant floor operations teams and enterprise IT/analytics functions.

Technologies

• GCP, Vertex AI
• BigQuery, Cloud Storage
• Dataform, Data Fusion, Astronomer
• SQL, Python

Benefits

• Immediate medical, dental, vision, and prescription drug coverage
• Flexible family care days
• Paid parental leave, new parent ramp-up programs, and subsidized back-up child care
• 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

Additional Information

• Job Type: Full time
• Work Type: Hybrid
• Tags: #LI-On-Site #LI-DS2