Global Data & AI Architecture Leader

Ford

Dearborn, Northern (MI, KY)

Hybrid

USD 180,000 - 240,000

Full time

6 days ago
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Job summary

Ford Motor Company in Dearborn, MI seeks a Principal Architect, Data, AI, and Analytics to lead a global team of 40+ architects and shape Ford's data strategy.

You will collaborate with Enterprise Technology and the Global Data & Analytics organization to ensure decisions are based on enterprise data, aligning data, AI, and analytics platforms with the long-term portfolio and roadmap. Requires deep experience in data architectures and leadership.

Qualifications

  • Bachelor's degree or equivalent in a relevant field.
  • 15+ years in IT or IT-focused business areas.
  • 10+ years building and architecting data-intensive applications.
  • 10+ years in Data, AI and Analytics systems.
  • Experience with cloud computing, especially Google Cloud Platform.
  • Experience applying data mesh, data lake, and related architectures.

Responsibilities

  • Lead a global team of 40+ architects guiding data, AI and analytics platforms.
  • Align data and analytics design with Ford's strategic portfolio and roadmaps.
  • Collaborate with security and Infrastructure to meet cybersecurity standards.
  • Advise and mentor leaders and engineers across the company.
  • Ensure architectures are scalable, reliable and meet business needs.

Skills

Influencing leaders
Strategic thinking
Team leadership
Architectural leadership
Cloud computing (GCP)
Data, AI and Analytics systems
Communication
Mentoring

Education

Bachelor's degree
Master's degree

Tools

Google Cloud Platform

Job description

Ford Motor Company in Dearborn, MI seeks a Principal Architect, Data, AI, and Analytics to lead a global team of 40+ architects and shape Ford's data strategy.

You will collaborate with Enterprise Technology and the Global Data & Analytics organization to ensure decisions are based on enterprise data, aligning data, AI, and analytics platforms with the long-term portfolio and roadmap. Requires deep experience in data architectures and leadership.

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