Head of Data Automation & Manufacturing Intelligence
6 days ago
San Jose
Job DescriptionSalary: About Ensurge Micropower Ensurge Micropower (OSE: ENSU) is a pioneer in solid-state microbattery technology, enabling the next generation of intelligent, connected devices. Leveraging proprietary thin-film and roll-to-roll manufacturing, Ensurge delivers safe, high energy-density batteries for applications in wearables, health tech, industrial sensing, and defense. With headquarters in San Jose and a global footprint spanning the U.S. and Europe, Ensurge is redefining what is possible in powering AI at the edge. Ensurgesolid-statemicrobatteriesoffer multiple times the energy density and charge cycles of lithium-ion alternatives.Our platform enables a wide range of battery shapes and form factors, unlocking new product designs and previously impossible applications Join our team of battery innovators in a dynamic, supportive start-up environment to enable the next generation of hearables, wearables, and IoT-connected sensors with Ensurges groundbreaking solid-statemicrobatteries. Role Overview Ensurge is seeking a Head of Data Automation & Manufacturing Intelligence to architect, build, and lead the companys end-to-end data, automation, and digital manufacturing ecosystem. This leader will be responsible for connecting the physical factory to digital intelligence spanning equipment control (PLC), SCADA, MES, cloud infrastructure, analytics, and AI/ML deployment. Reporting to the COO, this role is critical to Ensurges ability to scale with discipline, repeatability, and speed. This is not a tools administrator role. This is a hands-on systems architect and organizational leader who will define how data flows from machine process decision execution. We are building the operational backbone required to scale Ensurges breakthrough products and data is at the core of that mission. Key Responsibilities Manufacturing Automation & Control Systems • Own and standardize PLC architecture, communication protocols, and equipment integration across the factory, • Lead integration of SCADA systems for real-time monitoring, alarms, historical data, and visualization, • Partner with Equipment Engineering to embed data-first design into new tools and retrofits, • Establish automation standards for uptime, fault detection, interlocks, and safety MES, Traceability & Digital Manufacturing • Lead selection, implementation, and scaling of MES / MOM platforms to enable:, • Full product and process traceability, • Automated data capture (eliminating manual spreadsheets), • WIP, genealogy, yield, and cycle-time visibility, • Integrate MES with quality systems, travelers, and change control, • Ensure MES scales from pilot to volume without re-architecture Cloud, DevOps & Data Architecture • Design and own Ensurges cloud data architecture (AWS/Azure/GCP), • Build secure, scalable data pipelines from factory floor to cloud analytics, • Implement DevOps practices (CI/CD, infrastructure as code, monitoring, security), • Ensure data integrity, versioning, access control, and compliance readiness AI, Machine Learning & Advanced Analytics • Deploy AI/ML models for:, • Yield prediction and defect detection, • Equipment health and predictive maintenance, • Process optimization and DOE acceleration, • Translate manufacturing problems into data science use cases that deliver measurable ROI, • Partner with R&D, Manufacturing, and Quality to operationalize models not just prototype them APIs, Systems Integration & Data Products • Build robust API layers connecting PLCs, MES, LIMS, ERP, quality, and customer-facing systems, • Enable internal teams with self-service dashboards, alerts, and analytics, • Create standardized data products that support daily management, executive reviews, and board reporting Leadership, Strategy & Culture • Build and lead a high-performing automation, data, and software team, • Establish clear standards, documentation, and ownership models, • Serve as a key thought partner to the COO on scaling strategy, capacity modeling, and operational risk, • Embed a data-driven culture where decisions are visible, traceable, and fast What Were Looking For • Proven experience leading manufacturing data and automation systems in a high-tech production environment (semiconductor, battery, electronics, advanced manufacturing), • Deep hands-on expertise with:, • PLCs (Rockwell, Siemens, Beckhoff, or equivalent), • SCADA / HMI platforms, • MES / MOM systems, • Strong background in cloud platforms, DevOps, and modern software architecture, • Demonstrated experience deploying AI/ML models into production, not just research, • Ability to translate ambiguous manufacturing challenges into structured, scalable systems, • Familiarity with scaling data automation infrastructure to the varying needs of a developing manufacturing process, • Minimum Bachelors degree in Engineering, Computer Science, Data Science, or equivalent experience, • Located in, or willing toregularly workon-site in, the San Jose area Preferred Qualifications • Experience scaling from pilot manufacturing to volume production, • Familiarity with roll-to-roll processing, thin films, or semiconductor-style fabs, • Background integrating quality systems, traceability, and regulatory requirements, • Experience leading cross-functional teams spanning hardware, software, and operations, • Advanced degree in Engineering, Computer Science, Data Science, or equivalent experience Personal Attributes • Comfortable operating in a fast-moving, scaling environment with ambiguity and pressure, • Strong attention to detail paired with systems-level thinking, • Builders mindset pragmatic, hands-on, and outcome-oriented, • Collaborative, humble leader who elevates teams and sets high standards, • Curious, analytical, and relentlessly focused on learning and improvement