Prysmian is the world leader in the energy and telecom cable systems industry, seeking an Industrial Data Engineer to bridge Operations Technology and enterprise analytics. This role involves managing the flow of operational data and transforming it into actionable insights to enhance operational excellence and support AI initiatives.
Responsibilities:
- Own end-to-end data flow from OT historians (PI, Aveva, Ignition) to analytics and reporting environments
- Design, script, and maintain ETL/ELT pipelines for historian-to-cloud data movement using Python, SQL, and AWS services
- Develop reusable data models, APIs, and standardized data structures for use across plants and digital platforms
- Troubleshoot and resolve data flow disruptions, historian tag failures, and dashboard refresh issues
- Collaborate with plant engineers, OT, and IT teams to maintain secure, standardized, and reliable data pipelines
- Deliver automated, validated, and standardized dashboards and reports for OEE, downtime, scrap, and energy KPIs
- Develop APIs and data connectors to share information across MES, CMMS, and other digital platforms
- Ensure data models and structures are AI-ready for future machine-learning applications
- Standardize KPI definitions and data models across plants, allowing variation only where process differences require
- Integrate analytics and insights into operational processes and decision-making workflows
- Mentor junior analysts and plant associates, building local data literacy and self-service analytics capabilities
Requirements:
- 5+ years in a manufacturing analytics role
- Bachelor's degree in computer science, data science, or engineering
- Experience with AVEVA, Ignition, PLC tags required
- Willingness to travel at least 50% also required