Hybrid Vehicle Diagnostics & Data Systems Engineer

Ford; Dearborn (MI); Hybride; USD 109 000 - 170 000; Plein temps

Avantages offerts par ce poste

Medical coverage

Family care support

Vehicle discount program

Tuition assistance

Employee resource groups

Community service time off

Paid holidays

Additional vacation time

Résumé du poste

Ford Motor Company in Dearborn, Michigan, invites applications for a Diagnostics & Data Systems Engineer in a hybrid role combining remote and on-site work. You will design algorithms to analyze vehicle data streams, define data acquisition needs, and build cloud-native analytics to diagnose field issues.

Strong Python, CAN tools, and cloud experience are required. The role emphasizes root-cause analysis across AWS, Azure Data Explorer, and Google Cloud, with responsibilities that include

Qualifications

• Bachelor's degree or foreign equivalent in a related field and 3 years of relevant experience.
• Experience diagnosing battery drainage and applying problem-solving methodologies.
• Experience with CAN logs and data patterns to ensure network integrity.

Responsabilités

• Engineer and manage algorithms to analyze vehicle data streams for diagnostics.
• Define data acquisition requirements for onboard vehicle modules.
• Develop cloud-native tools and analytics platforms for rapid root-cause analysis.
• Analyze CAN logs to diagnose faults and improve diagnostic algorithms.
• Query and analyze large datasets from cloud platforms to extract insights.

Connaissances

Python scripting

CAN analysis

Vector CAN tools

Cloud data analysis

Testing & validation

Data querying

Electrical architecture

Formation

Bachelor's degree in Mechanical/Electrical/Data Science/CS or related field

Outils

Azure Data Explorer

AWS

Google Cloud

Description du poste

Ford Motor Company in Dearborn, Michigan, invites applications for a Diagnostics & Data Systems Engineer in a hybrid role combining remote and on-site work. You will design algorithms to analyze vehicle data streams, define data acquisition needs, and build cloud-native analytics to diagnose field issues.

Strong Python, CAN tools, and cloud experience are required. The role emphasizes root-cause analysis across AWS, Azure Data Explorer, and Google Cloud, with responsibilities that include