We’re looking for a Process Improvement Engineer who thrives on solving problems at the source. In this role, you’ll lead the charge in identifying operational breakdowns, digging into root causes, and designing smart, scalable solutions that prevent issues from recurring. You’ll work across teams to streamline workflows, improve reliability, and drive a culture of continuous improvement.
Key Duties:
Lead cross-functional process improvement efforts aimed at resolving recurring operational incidents and eliminating root causes.
Analyze workflows across departments to uncover inefficiencies, communication gaps, or systemic process failures.
Conduct detailed incident investigations using structured problem-solving tools (e.g., 5 Whys, fishbone diagrams, fault tree analysis).
Create scalable process fixes and preventive controls to reduce future incidents and boost reliability.
Work closely with engineering, operations, and ERP teams to implement improvements with minimal disruption.
Define, monitor, and report on KPIs related to process health, incident trends, and resolution effectiveness.
Develop clear documentation (SOPs, work instructions, process maps) to support consistency and accountability.
Provide training and coaching on root cause analysis and continuous improvement methodologies.
Requirements:
Bachelor’s degree in Industrial Engineering or related field (or equivalent experience).
3+ years in process improvement, root cause analysis, or industrial systems optimization.
Solid experience investigating operational issues and driving corrective actions.
Strong analytical skills with a bias toward action and data-backed decisions.
Comfortable working across departments and aligning different teams toward a shared solution.
Proficient in process mapping and structured problem-solving frameworks.
Preferences:
Use automation tools (e.g., Python, SQL) to streamline manual tasks and enable real-time process monitoring.
Lean Six Sigma certification or similar process improvement training.
Experience using process simulation or modeling tools.
Familiarity with supply chain or logistics operations.
Programming knowledge (e.g., Python, SQL) for data analysis and task automation.
Experience with ERP systems is helpful, but your ability to find the root of a problem matters more.
