Manufacturing Intelligence Engineer
Integrates data analytics and digital technologies to optimize industrial production and manufacturing performance.
Overview
This career involves the deployment of Industrial Internet of Things (IIoT) sensors and software to extract actionable insights from shop-floor machinery. The day-to-day rhythm alternates between technical system configuration and collaborative problem-solving with plant managers to address production bottlenecks. Professionals in this field spend significant time troubleshooting data pipelines and ensuring that automated systems provide accurate, high-frequency feedback to operators and executives.
The work feels technical and high-stakes, as system optimizations directly impact yield, energy consumption, and factory safety. Success in this role requires a blend of mechanical understanding and data engineering proficiency. Individuals who thrive in this career enjoy the tangible nature of physical production combined with the intellectual challenge of modernizing legacy industrial environments through software and advanced analytics.
Responsibilities
- Design and implement data acquisition systems to collect performance metrics from industrial machinery.
- Develop real-time dashboards that visualize production health and efficiency for factory leadership.
- Configure predictive maintenance algorithms to identify potential equipment failures before they occur.
- Standardize data protocols across diverse hardware sets to ensure seamless information flow.
- Collaborate with automation teams to integrate manufacturing execution systems with corporate data lakes.
- Audit data integrity and cybersecurity measures within the industrial control system network.
- Evaluate and pilot new digital technologies to improve overall equipment effectiveness.
Qualifications
- A bachelor degree in industrial engineering, computer science, or a related technical field is required.
- Extensive experience with industrial protocols such as MQTT, OPC-UA, or Modbus is essential.
- Proficiency in programming languages used for data processing, particularly Python or SQL, is mandatory.
- Demonstrated expertise in working with Manufacturing Execution Systems and SCADA platforms is necessary.
- Strong foundational knowledge of Lean Manufacturing principles and statistical process control is required.
Nice to have
- A Master degree in Data Science or Industrial Automation provides a competitive advantage.
- Professional certification in Six Sigma or similar quality management methodologies is highly valued.
- Experience with cloud infrastructure services like AWS IoT or Azure IoT Hub is preferred.
- Previous leadership of digital transformation or Industry 4.0 initiatives in a factory setting is beneficial.
Work environment
- Work is primarily conducted in a factory or plant environment with occasional office-based analysis.
- Collaboration occurs daily with maintenance technicians, plant managers, and software engineers.
- Standard full-time hours are common, though system deployments may require evening or weekend support.
- The role involves frequent use of industrial software, data visualization tools, and hardware diagnostic equipment.
Benefits & growth
- Compensation packages typically include base salary, performance bonuses, and comprehensive health benefits.
- Career progression often leads to roles such as Digital Transformation Lead or Director of Smart Manufacturing.
- Professional development is supported through specialized certifications in industrial cybersecurity and advanced analytics.
- Large organizations may offer relocation packages and opportunities to work across international plant networks.
See how Manufacturing Intelligence Engineer fits you
Take the free Apt quiz for a personalized match score, salary insights, and AI career coaching.
Take the free quiz