Description
At Ford, we believe freedom of movement drives human progress. To support this, we are transforming our data into an active, self-optimizing engine. This Director role will drive AI Readiness across the EDP by establishing engineering excellence, architectural standards, runbooks, and skills that all teams can leverage.
You will lead teams in defining how data is ingested, transformed, and represented within the EDP. You will partner closely with other leaders to build a platform that is self-healing, cost-efficient, and capable of supporting autonomous systems that can query, reason, and execute tasks. This is a role for a strategic thinker who is comfortable discussing semantic ontologies, distributed systems, and the organisational change required to lead a large-scale data transformation.
Responsibilities:
- 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 organisation 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.
Qualifications:
- 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.