Principal Specialist, Data Modeling & Architecture (OT)

About Maaden

Founded in 1997, Maaden has grown into one of the world’s fastest-expanding mining enterprises and stands as the Middle East’s largest diversified mining and metals group. The company is driving the expansion of Saudi Arabia’s mining sector as a key economic pillar through a globally integrated, end-to-end mining value chain. This position is an opportunity to contribute to that growth story and help shape the future of mining in the Kingdom.

Role Purpose

The Principal Specialist, Data Modeling & Architecture (OT) serves as the lead authority for building models for operational technology and industrial data. The role ensures that assets, events, measurements, and production contexts are represented consistently across plants, sites, and operational systems, enabling reliable OT analytics. It also defines common standards that connect historians, SCADA/DCS, condition monitoring, and maintenance data with enterprise IT data products.

This position is responsible for ensuring that OT-specific realities such as large time-series volumes, latency needs, site-to-site variation, and inconsistent connectivity are reflected in the design. The work centers on practical data patterns, semantic alignment, and governance built into the OT-to-IT integration approach.

Key Accountabilities

• Create and maintain standards for OT data modeling across time-series data, events, alarms, and asset structures to support operational analysis and reliability initiatives.
• Define core OT entities such as assets, tags, measurements, work-order relationships, and location hierarchies, and drive consistent use across locations and solutions.
• Develop integration patterns that connect OT measurements with enterprise entities to enable cross-functional reporting and performance insights.
• Build models that reflect historian behavior, including high-frequency data, compression, interpolation, and quality indicators, as well as streaming ingestion needs.
• Design scalable schemas for governed OT layers and OT data products, with traceability, lineage, and data-quality attributes included.
• Work closely with OT engineering, cybersecurity, and platform teams to ensure data flows are secure, segmented, and compliant.
• Evaluate OT solution designs and vendor outputs, acting as the design authority to resolve modeling decisions and protect long-term maintainability.
• Establish repeatable approaches for onboarding new sites and managing variation through naming standards, tag mapping, unit normalization, and reference data.
• Mentor engineers and modelers on OT semantics and modelling practices, and facilitate design reviews for high-priority OT programs.

Minimum Qualifications

• A bachelor’s degree in Computer Science, Engineering, Industrial Engineering, Data Engineering, or a similar discipline is required.
• A master’s degree is preferred, and prior experience with OT or industrial systems is an added advantage.

Minimum Experience

• 10 to 15 years of experience in data modeling or architecture, with clear exposure to OT or industrial data environments.
• Hands-on experience with historians, industrial protocols and systems, and the integration of OT data into enterprise analytics platforms.

Maaden High Performance Competencies

• Strategic thinking and decision-making ability to anticipate impact and guide enterprise direction.
• Collaboration and influencing skills to align stakeholders without direct authority.
• Execution excellence with a focus on high standards and measurable outcomes.
• Innovation and adaptability to apply modern approaches and evolve standards pragmatically.
• Change leadership to drive adoption, governance, and ongoing improvement.

Skills

• Strong grasp of OT data structures, including time-series information, events, alarms, quality flags, and asset hierarchies.
• Capability to model and combine OT and IT data for enterprise reporting and operational performance analysis.
• Working knowledge of SCADA/DCS, historians, sensors, and industrial operating contexts.
• Understanding of how reliability and maintenance data connect to OT datasets.
• Governance-first mindset covering data classification, access control, and auditability for industrial environments.
• Ability to engage effectively with plant operations, OT engineering, IT, and data platform teams.
• Experience with semantic data modeling and canonical data structures.
• Knowledge of data quality, lineage, and traceability practices.
• Ability to design scalable and reusable data architectures.

Location

Riyadh, Riyadh, Saudi Arabia.