Process Engineer

The Company

Dexcom Corporation (NASDAQ DXCM) is a pioneer and global leader in continuous glucose monitoring (CGM). Dexcom began as a small company with a big dream:
To forever change how diabetes is managed. To unlock information and insights that drive better health outcomes. Here we are 25 years later, having pioneered an industry. And we’re just getting started. We are broadening our vision beyond diabetes to empower people to take control of health. That means personalized, actionable insights aimed at solving important health challenges. To continue what we’ve started:
Improving human health.

Join a diverse and dynamic team of operations and engineers dedicated to delivering high-quality medical device products to patients around the world. Our team focuses on packaging, labeling, and distribution operations, working hands‑on with advanced, high-volume equipment to ensure products are delivered safely, efficiently, and in full compliance with regulatory standards.

We collaborate closely across Quality Engineering, Regulatory, R&D, Equipment Engineering, and Operations to design, optimize, and sustain robust processes. We drive improvements in throughput and quality while supporting new product and material introductions, ensuring reliable, scalable operations that directly impact business performance and patient outcomes.

In this role, you will own defined areas of process performance for packaging and labeling operations, driving measurable improvements in quality, delivery, and cost. You’ll use data and engineering fundamentals while partnering cross‑functionally to develop and improve scalable, compliant processes that directly support Dexcom’s mission to improve the lives of people with diabetes.

• Drive KPI improvements by analyzing manufacturing data and supporting continuous improvement initiatives across packaging and labeling operations
• Troubleshoot and support packaging and labeling equipment, ranging from manual to automated systems, to resolve process issues
• Lead or contribute to cross‑functional teams in structured problem solving to identify root causes and implement sustainable solutions that improve yield, quality, and reliability
• Design, document, and improve manufacturing processes, equipment, and standard work within a regulated quality system
• Execute equipment qualifications and process validations (IQ/OQ/PQ), including DOE development, statistical analysis, and technical reporting
• Apply statistical methods (SPC, capability analysis, MSA, Pareto) to identify opportunities and improve throughput, efficiency, and product quality
• Support new product and process introductions, scaling from prototype to full production while defining robust manufacturing and equipment requirements
• Partner closely with Quality, Regulatory, R&D, Operations, and Engineering to ensure compliant, patient‑focused solutions
• Evaluate and improve manufacturing operations, including capacity planning, line design, workflow optimization, and equipment utilization

• Experience working with manufacturing processes, preferably in packaging, labeling, or high‑volume production environments
• Strong data analysis skills with the ability to build, interpret, and present KPI dashboards to drive decision‑making
• Proven ability to manage self‑directed projects—prioritizing work, meeting deadlines, and delivering results in a fast‑paced environment
• Hands‑on mindset with demonstrated success working directly with equipment, processes, or manufacturing operations
• Experience applying structured problem‑solving methodologies (e.g., DMAIC, root cause analysis) to drive measurable improvements
• Ability to prioritize effectively and adapt to changing business needs while maintaining commitments
• Strong cross‑functional collaboration skills across engineering, quality, regulatory, and operations teams
• Experience working in regulated environments (e.g., medical device, pharma, or similar quality systems)
• Familiarity with basic coding or scripting (e.g., Python, SQL, or similar) to support data analysis, automation, and process insights
• Exposure to statistical methods and tools (e.g., SPC,…