Principal Specialist, Data Modeling & Arch (OT)

Role Overview

Principal Specialist, Data Modeling & Architecture (OT) at Ma'aden in Saudi Arabia. This role serves as the architectural authority for operational technology (OT) and industrial data modeling across the organization's mining operations.

Company Overview

Ma'aden, established in 1997, is one of the fastest-growing mining companies in the world and the largest multi-commodity mining and metals company in the Middle East. The company is leading the development of the mining industry to become the third pillar of Saudi Arabia's economy by building a world-class, unique, and fully integrated mining value chain.

Role Purpose

Ensure consistent representation of assets, events, measurements, and production contexts across plants, sites, and operational systems. Enable trusted OT analytics by defining standard models that align historians, SCADA/DCS, condition monitoring, and maintenance data with enterprise IT data products. Address OT constraints—including high-volume time-series data, latency requirements, site variability, and intermittent connectivity—through practical modeling patterns, semantic consistency, and governance-by-design across OT-to-IT integration.

Key Responsibilities

Data Modeling Standards

• Define OT data modeling standards for time-series, events, alarms, and asset hierarchies to support operational analytics and reliability use cases.
• Establish canonical OT concepts including asset, tag, measurement, work order linkage, and location hierarchy.
• Ensure consistent adoption of modeling standards across sites and solutions.

OT-to-IT Integration

• Architect OT-to-IT data alignment patterns that map operational measurements to enterprise entities for cross-domain reporting and performance analysis.
• Ensure OT models account for historian characteristics including high frequency, compression, interpolation, and quality flags.
• Ensure OT models account for streaming ingestion patterns.
• Define reusable patterns for site onboarding and variability handling, including naming normalization, tag mapping, unit standardization, and reference data.

Schema Design & Governance

• Design scalable schemas for curated OT layers and OT data products, including auditability, lineage, and quality attributes.
• Partner with OT engineering, cyber/security, and platform teams to ensure secure, segmented, and compliant design for OT data flows.

Design Authority & Coaching

• Review OT data solution designs and vendor deliverables.
• Provide design authority to resolve modeling trade-offs and ensure long-term maintainability.
• Coach engineers and modelers on OT semantics and modeling best practices.
• Lead design reviews for critical OT initiatives.

Qualifications & Experience

Education

• Bachelor's degree in Computer Science, Engineering, Industrial Engineering, Data Engineering, or related field.
• Master's degree preferred.
• OT/industrial systems background is an advantage.

Experience

• 10–15 years of experience in data modeling and architecture with demonstrated exposure to OT and industrial data landscapes.
• Experience working with historians, industrial protocols and systems.
• Experience integrating OT data into enterprise analytics platforms.

Skills & Competencies

Technical Skills

• Deep understanding of OT data characteristics including time-series, events, alarms, and quality flags.
• Deep understanding of asset hierarchies.
• Ability to model and integrate OT and IT data for enterprise analytics and operational performance reporting.
• Knowledge of SCADA, DCS, historians, sensors, and industrial context.
• Familiarity with reliability and maintenance data linkages.
• Strong governance-by-design mindset including classification, access control, and auditability for industrial data.

Competencies

• Strategic Thinking & Decision Making – Anticipates implications and guides enterprise direction.
• Collaboration & Influencing – Aligns diverse stakeholders without direct authority.
• Execution Excellence – Sets high standards and ensures measurable outcomes.
• Innovation & Adaptability – Applies modern practices and evolves standards pragmatically.
• Change Leadership – Drives adoption, governance, and continuous improvement.
• Stakeholder engagement across plant and site operations, OT engineering, IT, and data platform teams.