Principal Specialist, Data Modeling & Architecture (Operational Technology)

Job Summary

Establish data modeling and architecture standards for Operational Technology and industrial data across plants and operational systems. Enable trusted OT analytics by standardizing how assets, tags, events, alarms, measurements, and maintenance data are represented, governed, and aligned with enterprise IT data products.

Responsibilities

• Define enterprise OT data modeling standards for time-series data, events, alarms, assets, tags, measurements, and production contexts.
• Establish canonical OT concepts including asset hierarchy, location hierarchy, tag naming, measurement definitions, and work order linkage.
• Design scalable data schemas for curated OT layers and reusable OT data products with auditability, lineage, and quality attributes.
• Architect OT-to-IT data alignment patterns connecting operational measurements with enterprise entities for reporting and analytics.
• Embed governance-by-design into OT data models, including ownership, metadata, lineage, quality rules, and lifecycle controls.
• Partner with OT engineering, cybersecurity, data platform, and infrastructure teams to design secure and compliant OT data flows.
• Provide technical leadership on OT semantics, industrial data architecture, and data modeling practices to engineers and platform teams.
• Lead design reviews for critical OT data initiatives and build knowledge assets, standards, and reference patterns for consistent delivery.

Requirements

• Bachelor’s Degree in Computer Science, Computer Engineering, Data Engineering, Industrial Engineering, Information Systems, or related discipline. Master’s Degree preferred.
• Minimum 10 years of progressive experience in data modeling, data architecture, data engineering, industrial data platforms, or OT/IT integration.
• Strong exposure to operational technology data sources such as historians, SCADA/DCS, condition monitoring, maintenance, reliability, and production systems.
• Demonstrated experience defining enterprise data models, data standards, semantic layers, governance controls, and scalable data product architectures.
• Expertise in OT data modeling and industrial data architecture.
• Knowledge of time-series data, historians, SCADA/DCS, events, alarms, and tag structures.
• Experience with asset hierarchy, location hierarchy, measurement models, and semantic standardization.
• Proficiency in data product design, curated data layers, metadata, lineage, and quality management.
• Understanding of industrial cybersecurity awareness and secure OT data flow design.
• Capability in architecture review, stakeholder collaboration, coaching, and technical documentation.

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