Be at the forefront of Ford’s product transformation!
We are seeking a highly specialized and experienced Product Structure Transformation Lead to spearhead a critical, company-wide initiative focused on fundamentally reshaping Ford’s product data landscape. This role offers a unique opportunity to define the future of Ford’s product data through the application of advanced architectural principles and the development of intelligent, programmatic solutions.
The ideal candidate will be a seasoned architect with a deep, nuanced understanding of complex product structures, proven expertise in data transformation, and a profound grasp of product architectural elements and their underlying logic. This role requires a scientific and focused approach to decompose, define, and translate intricate product data. Responsibilities include in-depth analysis of current product data architectures, defining foundational elements, meticulously mapping data to a future state, developing sophisticated transformation logic, and collaborating with cross-functional teams to execute this precise data transformation at scale using programmatic accelerators.

MINIMUM REQUIREMENTS:

• Bachelor’s degree in mechanical engineering
• 15+ years of experience in Product Development/ Transformation function.
• 8+ years in automotive industry; High-Tech, Industrial products.
• 5+ years expertise in re-architecting Product Structures.
• 3+ years, around product architecture design, modularity, platform engineering.
• 3+ years of experience in data transformation concepts like logic design, transformational frameworks, canonical data models.
• Travel within North American countries (including USA and Mexico) will be required, including supporting launch programs.

PREFERRED REQUIREMENTS

• Proficiency in deep principles of rule engines used for defining and managing complex product configurations and relationships.
• Proven experience of implementing PLM systems and other enterprise tools at a large, complex organization.
• Academically sound with industry leading concepts with implementation experience
• Experience in the field of data analytics, reporting and AI
• Knowledge of composite AI, LLM Model, prompt engineering and orchestration
• Proven capability to create indices to measure the cost of variety within product portfolios.In-depth knowledge of product development processes and product data release frameworks.
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  Successful canddates will be required to provide proof of degree completion for the highest level of education attained. If the degree was obtained from a school outside of Canada, an Education Credential Assessment report showing Canadian equivalency is also required.
  We thank all applicants for their interest, but only those selected for an interview will be contacted.
  Ford of Canada is an Equal Opportunity Employer and is committed to a culturally diverse workforce. Accommodations for applicants with disabilities throughout the recruitment, selection and / or assessment processes, where needed, are available upon request. Please inform Human Resources of the nature of any accommodation(s) that you may require.
  Candidates for this position must be legally entitled to work in Canada. Ford Motor Company of Canada, Limited does not sponsor work permit applications.

Current State Architectural Analysis: Conduct comprehensive analysis of existing product structures, identifying architectural patterns, data flows, and interdependencies.
Structure Decomposition: Decompose complex product structures into foundational data objects and elemental components (e.g., entities, business objects, relationships, data fields).
Value Identification: Determine value-added vs. non-value-added entities within the current product data landscape, guiding optimization efforts.
Future State Product Architecture Definition: Collaborate with cross-functional teams to define the desired future product structure, incorporating advanced architectural principles.
Elemental Datasets (Future): Understand and define decomposed elemental datasets required for the future state product architecture.
Element Mapping: Meticulously map current state product data elements to future state elements, ensuring precise translation paths.
Transformation Logic Development: Develop sophisticated transformation logic and translate these into robust, scalable “programmatic accelerators” for automated data processing.
Large-Scale Data Structure Design and Translation: Oversee and execute the translation of current state product datasets into future state datasets at scale, leveraging developed accelerators