Data Engineer: Automation & Controls for Plant Startup

Ford Motor Company; Marshall (MI); On-site; USD 65,000 - 166,000; Full time

Benefits offered by this job

Medical, dental, vision coverage

Paid time off

Vehicle discount program

Tuition assistance

Job summary

Ford Motor Company is building a state-of-the-art manufacturing facility in Michigan and seeks a data engineer to help transform production data into actionable insights. You will develop data pipelines, automate repetitive tasks, and connect enterprise systems to enable real-time analytics across the plant floor.

You’ll work on standardizing processes, ensuring safety, quality, and governance while collaborating with IT, Manufacturing Engineering, and operations teams.

Qualifications

• Bachelor’s degree required; Master’s preferred in engineering or CS.
• 4+ years of data engineering experience.
• 2+ years of data visualization (reports, dashboards).
• 2+ years of programming in Python, SQL, C++, or Java for automation and data processing.

Responsibilities

• Ensure adherence to FPS KUP and manufacturing OS principles.
• Develop data pipelines and automate repetitive data tasks.
• Connect enterprise apps and manufacturing systems via APIs and messaging.
• Profile, map, and model data to ensure governance and accuracy.
• Troubleshoot PLC/robot automation and resolve downtime.
• Lead and train teams; drive continuous improvement and change control.

Skills

Data engineering

Data visualization

Python

SQL

C++

Java

Education

Bachelor's degree in engineering or CS

Master’s degree in engineering or computer science

Tools

Power BI

APIs

PLC programming

Job description

Ford Motor Company is building a state-of-the-art manufacturing facility in Michigan and seeks a data engineer to help transform production data into actionable insights. You will develop data pipelines, automate repetitive tasks, and connect enterprise systems to enable real-time analytics across the plant floor.

You’ll work on standardizing processes, ensuring safety, quality, and governance while collaborating with IT, Manufacturing Engineering, and operations teams.