Data Engineering Manager

Ford Ford · Auto · Dearborn, MI +1 · Enterprise Technology

This role is for a Data Engineering Manager at Ford Pro 360, focused on designing and maintaining enterprise data architecture to support AI monetization and Agentic AI workflows. The role involves leading data engineering initiatives, ensuring data governance, and enabling AI/ML models and GenAI infrastructure.

What you'd actually do

  1. Lead Data Engineering: Drive the development of real-time and batch data pipelines, manage GCP infrastructure, ensure code quality, and oversee integrations with downstream systems like Salesforce and Marketing Cloud.
  2. Drive AI Data Initiatives: Architect data foundations to support AI monetization, including predictive analytics and cutting-edge Agentic AI workflows leveraging Google Vertex AI and Gemini.
  3. Enforce Data Governance: Implement "Policy as Code," machine-readable data contracts, data quality observability, and strict privacy controls (GDPR, CCPA, PRO ID management).
  4. Lead Engineering Execution: Manage and mentor pods of data and software engineers to design, build, and deploy domain-driven data products on Google Cloud Platform (BigQuery, Dataflow, Pub/Sub, Cloud Composer/Airflow).
  5. AI Data Readiness: Architect and optimize data models to support high-priority machine learning initiatives ensuring training and inference pipelines are highly available and scalable.

Skills

Required

  • Data Engineering
  • Data Architecture
  • AI/ML Ops
  • Technical Leadership
  • Google Cloud Platform (GCP) data services (BigQuery, Cloud Composer, Dataflow, Pub/Sub, Dataplex)
  • Operationalizing AI/ML models
  • GenAI/Agentic AI infrastructure (Vertex AI, LLM orchestration)
  • Python
  • SQL
  • Terraform/IaC
  • Customer Data Platforms (CDPs)
  • Master Data Management (MDM)
  • Salesforce integration
  • Enterprise billing/financial data flows
  • Enterprise data governance
  • Data contracts
  • Global privacy regulations (GDPR, CCPA)

Nice to have

  • Bachelor’s / Masters’s Degree in Computer Science, Data Engineering, Information Technology, or a related technical field
  • SonarQube 'A' ratings
  • CI/CD automation
  • DataOps packages
  • legacy tech debt decommissioning
  • Federated Data Sharing
  • role-based and attribute-based access controls

What the JD emphasized

  • Google Cloud Platform (GCP)
  • AI/ML models
  • GenAI/Agentic AI infrastructure
  • Python
  • SQL
  • Terraform/IaC
  • Customer Data Platforms (CDPs)
  • Master Data Management (MDM)
  • Salesforce
  • GDPR
  • CCPA

Other signals

  • architect data foundations to support AI monetization
  • cutting-edge Agentic AI workflows
  • support AI/ML models and supporting GenAI/Agentic AI infrastructure