Principal Specialist, Data Modeling & Arch (OT)

Maaden, 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. We are 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. We are pleased to share an exciting opportunity for the below mentioned position. This role offers a chance to contribute to our ambitious growth and play a key part in shaping the future of mining in the Kingdom.

The Principal Specialist, Data Modeling & Architecture (OT) is the architectural authority for modeling operational technology (OT) and industrial data, ensuring consistent representation of assets, events, measurements, and production contexts across plants, sites, and operational systems. The role enables trusted OT analytics by defining standard models that align historians, SCADA/DCS, condition monitoring, and maintenance data with enterprise IT data products.

The position ensures OT constraints—such as high-volume time-series data, latency requirements, site variability, and intermittent connectivity—are addressed through practical modeling patterns, semantic consistency, and governance-by-design across OT-to-IT integration.

1. Define OT data modeling standards for time-series, events, alarms, and asset hierarchies to support operational analytics and reliability use cases.
2. Establish canonical OT concepts (asset, tag, measurement, work order linkage, location hierarchy) and ensure consistent adoption across sites and solutions.
3. Architect OT-to-IT data alignment patterns that map operational measurements to enterprise entities for cross-domain reporting and performance analysis.
4. Ensure OT models account for historian characteristics (high frequency, compression, interpolation, quality flags) and streaming ingestion patterns.
5. Design scalable schemas for curated OT layers and OT data products, including auditability, lineage, and quality attributes.
6. Partner with OT engineering, cyber/security, and platform teams to ensure secure, segmented, and compliant design for OT data flows.
7. Review OT data solution designs and vendor deliverables; provide design authority to resolve modeling trade-offs and ensure long-term maintainability.
8. Define reusable patterns for site onboarding and variability handling (naming normalization, tag mapping, unit standardization, reference data).
9. Coach engineers and modelers on OT semantics and modeling best practices; lead design reviews for critical OT initiatives.

• 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.

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

• 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.

• Deep understanding of OT data characteristics (time-series, events, alarms, quality flags) and 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/maintenance data linkages.
• Strong governance-by-design mindset including classification, access control, and auditability for industrial data.
• Stakeholder engagement across plant/site operations, OT engineering, IT, and data platform teams.