# Senior Data Scientist / ML Engineer

**Company**: Ford Motor Company
**Location**: Redford, MI
**Work arrangement**: hybrid
**Experience**: senior
**Job type**: full-time
**Salary**: $132,800-$250,800
**Category**: IT
**Industry**: Automotive
**Wikidata**: https://www.wikidata.org/wiki/Q44294

**Apply**: https://efds.fa.em5.oraclecloud.com/hcmUI/CandidateExperience/en/sites/CX_1/job/70439?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_58340a6d-714

## Description

We are seeking a Senior Data Scientist / ML Engineer to join our team at Ford Motor Company. As a Senior Data Scientist / ML Engineer, you will play a critical role in designing and evolving Ford's data mesh architecture across manufacturing and enterprise domains.

**Data Mesh Strategy & Architecture**

- Design and evolve Ford's data mesh architecture across manufacturing and enterprise domains , defining domain boundaries, data product contracts, and interoperability standards.

- Establish and maintain federated computational governance policies applied consistently across decentralized domain teams.

- Champion adoption of next-generation technologies and cloud-native patterns to modernize legacy data workflows and drive measurable business impact.

**Data Product Development**

- Lead the transformation of raw data into curated, documented, high-quality data products.

- Define and enforce data product standards: ownership, schema versioning, SLAs for freshness/completeness/accuracy, discoverability, and access controls.

- Oversee the build-out of ingestion, transformation, and publishing pipelines that convert raw operational data into standardized, reusable data assets.

- Design and build data structures and semantic layers that enable AI agents to interpret enterprise data consistently and with minimal human intervention.

**Data Modeling & Architecture**

- Design and develop data models for assigned domains; manage and maintain models in a shared repository.

- Partner with product and analytics teams to translate use cases into data requirements, providing architecture guidance, data models, and design reviews.

- Establish and enforce data architecture principles, standards, and best practices across the team's data products.

- Drive data quality initiatives: profile source-system data, define data quality requirements and metrics, and guide monitoring, measurement, reporting, and remediation.

**Platform & Tooling**

- Drive adoption of cloud services like GCP as the technical backbone of 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.

**Governance & Compliance**

- Own and evolve the federated governance framework, balancing global standards with domain-level autonomy, ensuring compliance with Ford's data security, privacy, and regulatory requirements.

- Implement automated policy enforcement via 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.

**Qualifications**

- 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.

- 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.

## Skills

### Required
- GCP
- BigQuery
- Cloud Storage
- Dataform
- Data Fusion
- Astronomer
- Python
- SQL
- data modeling
- data governance
- data quality
- AI/ML
- semantic layers
- knowledge graphs
- ontologies

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Source: [Apply at efds.fa.em5.oraclecloud.com](https://efds.fa.em5.oraclecloud.com/hcmUI/CandidateExperience/en/sites/CX_1/job/70439?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)