About the job
About Us:
At Challenge Manufacturing, our mission is to achieve operational excellence through the empowerment of our employee-owners. As a prominent tier 1 supplier of intricate metal assemblies in the global automotive sector, we are committed to pioneering innovative solutions for future mobility. We believe that the best ideas stem from diverse perspectives, and when these ideas are combined with the collaborative efforts of industry leaders, we can overcome any challenge. Our team members take immense pride in their contributions and consistently uphold our core values of safety, ownership, and teamwork; they are the true driving force behind our operations.
We are honored to be one of the largest employee-owned automotive companies in North America. A notable benefit of joining the Challenge team is our ESOP program, which grants shares of the Company to all employee-owners annually. This program serves as a valuable retirement benefit that continues to grow throughout your tenure at Challenge. Being part of an ESOP means sharing in the success of Challenge!
Challenge is #QualityDriven and #PeoplePowered!
Who We Are Looking For:
We are in search of a strategic and proactive Digital Analytics & IIoT Manager to spearhead the collection, integration, and analysis of plant-floor data across a high-volume automotive manufacturing network. This role is pivotal in transforming MES/SCADA, PLC, and IIoT data into actionable insights that enhance production efficiency, uptime, quality, and predictive maintenance.
The ideal candidate will possess a robust background in industrial analytics, IIoT implementation, and automotive manufacturing operations, with the ability to collaborate effectively across Production, Maintenance, Engineering, OT, and IT teams to deliver scalable, data-driven solutions that support vehicle launches, high-volume production schedules, and continuous improvement initiatives.
Responsibilities:
- Oversee the design, deployment, and management of industrial data pipelines for MES/SCADA, PLCs, and IIoT sensors across multiple facilities.
- Implement digital twins, real-time monitoring dashboards, and predictive maintenance models to mitigate unplanned downtime and optimize asset utilization.
- Develop and sustain KPIs, operational dashboards, and reporting tools aimed at enhancing throughput, OEE, cycle times, first-pass yield, scrap reduction, and energy consumption.
- Integrate IIoT devices and industrial sensors with OT systems, MES/SCADA, ERP, and analytics platforms to ensure seamless end-to-end visibility.
- Collaborate with Production, Maintenance, and Quality teams to pinpoint bottlenecks, optimize processes, and implement data-driven improvements.

