Manager, Data Architecture

At Ford Motor Company, we believe freedom of movement drives human progress. We are shaping the future of mobility through connected vehicles, intelligent products, and data-driven decision-making - and data is foundational to that future.

Ford’s Global Data Insights & Analytics organization enables the enterprise to transform data into trusted, reusable, and actionable products. We partner with business, product, engineering, analytics, and AI teams to make Ford’s data easier to discover, understand, govern, and use at scale.

As a Cloud Data Architect, you will work across domains to translate business outcomes into scalable, secure, governed, and reusable data designs. You will establish architecture patterns and guardrails, guide teams through onboarding and implementation, and ensure data products are built with the quality, interoperability, semantic context, and operational rigor required for enterprise use.

• Define and evolve cloud data architecture patterns, standards, reference architectures, and roadmaps in partnership with Data Product Management, Enterprise Architecture, platform engineering, governance, security, and domain teams.
• Partner with business and technology stakeholders to translate strategic business needs into scalable data architecture, data-product, and integration designs.
• Guide teams in designing and implementing trusted, reusable, discoverable, and well-governed data products.
• Develop and govern conceptual and logical data models for enterprise and domain data products.
• Establish standards for data modeling, naming, schema design, data contracts, lineage, metadata, master/reference data, data quality, and lifecycle management.
• Drive adoption of metadata-management and semantic capabilities, including the use of ontology-based business rules and semantic models where appropriate to support analytics and AI/agentic use cases.
• Partner with domain teams to understand their data landscape, assess architecture readiness, identify capability gaps, and define practical improvement plans.
• Serve as an architecture advisor and trusted point of contact for teams navigating the enterprise data ecosystem, helping connect them to the appropriate platform, product, governance, and enablement partners.
• Define and promote reusable architecture patterns that reduce duplicate data movement, improve interoperability, and enable self-service consumption.
• Ensure architecture designs meet requirements for security, privacy, compliance, resiliency, observability, data quality, and cost optimization.
• Review solution designs and provide architecture guidance throughout the delivery lifecycle, balancing enterprise standards with business speed and practical implementation needs.
• Collaborate with engineering teams to improve the usability and adoption of platform capabilities by identifying recurring customer friction, handoff gaps, and onboarding challenges.
• Evaluate emerging cloud, data, metadata, semantic, and AI technologies and recommend where they can create value for Ford.

• Communicate architecture decisions, tradeoffs, standards, and roadmaps clearly to both technical and non-technical audiences.

Minimum Qualifications

• Bachelor’s degree in Computer Science, Data Engineering, Information Systems, Analytics, or a related field, or equivalent professional experience.
• 3+ years of experience in data architecture, data engineering, solution architecture, or a related technical role.
• Experience designing and delivering modern cloud-based data platforms, pipelines, or data products in GCP, AWS, Azure, or a comparable cloud environment.
• Strong experience with data modeling, including conceptual, logical, and physical models for operational, analytical, and event-driven use cases.
• Experience with structured, semi-structured, and unstructured data; relational and NoSQL data stores; and data lake, lakehouse, warehouse, and data-mesh/data-product concepts.
• Strong SQL skills and experience using Python, Java, Scala, or similar languages for data processing, automation, and integration.
• Experience with distributed data-processing and streaming technologies, such as Apache Spark, Kafka, Pub/Sub, Dataflow, Flink, or comparable services.
• Experience with data governance, metadata management, data lineage, data quality, security, and privacy practices.
• Ability to influence across organizational boundaries and work effectively with product managers, engineers, data stewards, domain leaders, and executive stakeholders.
• Strong written, verbal, and visual communication skills, including the ability to communicate complex architecture concepts in clear business terms.

Preferred Qualifications

• Experience with Google Cloud Platform data services, including BigQuery, Cloud Storage, Pub/Sub, Dataflow, Dataproc, Composer, Dataplex, Data Catalog, and related services.
• Experience designing event-driven and real-time data architectures.
• Experience defining data contracts, reusable data-product standards, and domain-oriented data architecture practices.
• Experience with semantic technologies, ontologies, knowledge graphs, or enterprise semantic models that enable trusted business rules and AI/agent use cases.
• Experience with data cataloging, metadata platforms, and data observability tools.
• Experience with DevSecOps, infrastructure as code, CI/CD, automated testing, and architecture-as-code practices.
• Experience supporting AI, machine learning, generative AI, or agentic AI solutions through well-governed data and semantic foundations.
• Experience in a large, complex enterprise environment with diverse business domains, legacy systems, and modern cloud platforms.

• Automotive, manufacturing, mobility, financial, supply-chain, or connected-product data experience.