Advanced Manufacturing Process Engineer

Central Power Systems & Services•Tracy, MO

3d•Onsite

About The Position

This is a senior-level role for someone who has operated at the intersection of manufacturing operations and digital transformation. The Advanced Manufacturing Process Engineer owns three things simultaneously in year one: documenting and standardizing how CPSS operates today, identifying where technology closes the gap between current and future state, and tracking the KPIs that tell leadership whether any of it is working. This role is the connective tissue between the shop floor and the Digital Transformation team—translating operational reality into system requirements, and translating system outputs back into operational decisions. CPSS is actively scaling. The person in this role will help define what the company looks like operationally as it grows, and will have a seat at the table when those decisions get made.

Requirements

Bachelor’s degree in Engineering, Manufacturing, Industrial Engineering, Information Systems, or related field
6+ years of experience in manufacturing operations, process engineering, or business analysis in a discrete manufacturing environment
Process documentation & mapping: Demonstrated ability to document complex manufacturing processes, build future-state models, and drive standardization across operations
KPI ownership: Experience defining, tracking, and presenting manufacturing performance metrics to operations leadership
Cross-functional translation: Proven ability to capture business requirements from operations and translate them into clear functional specifications for technical teams
Must live in or be willing to relocate to the Kansas City, Missouri area

Nice To Haves

Experience with MES, ERP systems (Epicor experience a plus), or industrial data platforms in a discrete manufacturing context
Lean manufacturing or Six Sigma certification; hands-on application in a production environment
Exposure to IIoT, automation, or smart factory initiatives
Working knowledge of SQL, data analysis, or BI/reporting tools
Familiarity with cloud data integration and OT/cybersecurity principles in manufacturing environments
Experience with process mapping tools (Visio, BPMN)

Responsibilities

Document current-state manufacturing processes, workflows, and SOPs across all production operations—laser, brake, panel bender, punch, paint, and support functions.
Develop future-state process models aligned with digital transformation goals and production scaling requirements.
Drive process standardization across facilities, cells, and—as the company grows—across facilities.
Maintain a living process library that serves as the operational foundation for system configuration, training, and continuous improvement.
Own the definition, data sourcing, and tracking of key manufacturing KPIs—OEE, scrap, on-time delivery, labor efficiency, and inventory performance.
Partner with the Digital Transformation team to ensure KPIs surface in dashboards and reporting tools in a form that is actionable, not decorative.
Identify gaps between what the business needs to measure and what the current data infrastructure can produce—and drive closure of those gaps.
Support continuous improvement initiatives by translating performance data into structured problem statements and improvement hypotheses.
Serve as the primary translator between operations and the technical team—capturing business needs, facilitating process mapping sessions, and producing functional requirements that engineers can build from.
Support implementation of digital tools including MES, ERP integrations, data platforms, and automation solutions by ensuring the process side of the equation is solved before the system side is built.
Facilitate stakeholder workshops and floor-level interviews to surface operational requirements that don’t appear in system data.
Drive change management and user adoption for new digital solutions—ensuring tools get used, not shelved.
Identify inefficiencies, bottlenecks, and waste across manufacturing workflows using both qualitative floor observation and quantitative data analysis.
Apply lean and structured problem-solving frameworks to develop and validate improvement recommendations before technology solutions are scoped.
Partner with operations, engineering, quality, and the Ops & Technology team as a cross-functional contributor—not a siloed analyst.