Principal Specialist, Data Modeling & Arch (Operational Technology)

Ma'aden Aluminium Company (MAC); Medina; On-site; SAR 420,000 - 660,000; Full time

Job summary

Ma'aden Aluminium Company (MAC) is seeking a senior OT data strategist to establish modeling standards and architecture for industrial OT data across plants and systems. You will standardize asset tags, events, alarms, and measurements to enable trusted OT analytics.

You will also align OT data with enterprise IT data products, ensuring quality, lineage, and governance while addressing high-volume and intermittent connectivity challenges.

Qualifications

• Bachelor level degree in a related discipline is required to support OT data modeling and architecture work.
• Master's degree is preferred for advanced data governance and architecture leadership.
• Experience in OT/IT data integration and data product design is essential.

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/location hierarchies, tag naming, and measurement definitions.
• Design scalable schemas for OT data layers and reusable data products with auditability and quality attributes.
• Architect OT-to-IT data alignment patterns and integration rules for cross-site normalization.
• Institute governance patterns with ownership, lineage, and lifecycle controls.

Skills

OT data modeling & architecture

Time-series data

Historians/SCADA/DCS

Asset hierarchy & location

Data governance & lineage

Data product design

Streaming ingestion

Industrial cybersecurity awareness

Architecture reviews & documentation

Education

Bachelor's Degree in Computer Science/Engineering or related

Master's Degree preferred

Job description

Why This Role Matters

This role establishes the data modeling and architecture foundation for Operational Technology OT and industrial data across plants sites and operational systems It enables trusted OT analytics by standardizing how assets tags events alarms measurements production contexts historians SCADA DCS condition monitoring and maintenance data are represented governed and aligned with enterprise IT data products

What You Will Deliver

OT Data Modeling Standards & Architecture

• 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
• Ensure modeling patterns address high-volume industrial data latency requirements site variability and intermittent connectivity

OT-to-IT Data Alignment & Integration

• Architect OT-to-IT data alignment patterns that connect operational measurements with enterprise entities for reporting and analytics
• Align historians SCADA DCS condition monitoring maintenance reliability and production data with enterprise data products
• Define integration rules for tag mapping unit standardization reference data semantic consistency and cross-site normalization
• Support cross-domain analytics by ensuring OT data is usable for reliability production performance safety sustainability and cost insights

Industrial Data Governance & Quality

• Embed governance-by-design into OT data models including ownership metadata lineage quality rules and lifecycle controls
• Define quality attributes for historian data including compression interpolation quality flags sampling frequency and streaming patterns
• Establish reusable governance patterns for site onboarding data standardization naming conventions and master reference data alignment
• Ensure OT data products are traceable reliable maintainable and aligned with platform architecture standards

Security Compliance & Solution Design Authority

• Partner with OT engineering cybersecurity data platform and infrastructure teams to design secure and compliant OT data flows
• Ensure OT data architecture respects segmentation access control operational resilience and industrial cybersecurity requirements
• Review solution designs data models vendor deliverables and integration approaches to ensure architectural consistency
• Resolve modeling trade-offs and guide design decisions to support long-term scalability maintainability and operational reliability

Technical Leadership Coaching & Knowledge Transfer

• Provide technical leadership on OT semantics industrial data architecture data modeling practices and data product design
• Coach engineers data modelers platform teams and solution teams on OT modeling standards and implementation practices
• Lead design reviews for critical OT data initiatives and ensure decisions are documented and reusable across sites
• Build knowledge assets standards templates and reference patterns to accelerate consistent OT data architecture delivery

What Success Looks Like

Standard OT data models are defined and adopted consistently across sites platforms and industrial systems Assets tags events alarms measurements and production contexts are represented consistently for trusted analytics OT-to-IT integration patterns enable reliable cross-domain reporting performance analysis and data product development Curated OT layers include clear lineage quality rules auditability and governance controls Site onboarding tag normalization unit standardization and data model reuse are accelerated through practical reference patterns

Experience

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

Skills That Matter

• OT data modeling and industrial data architecture
• Time-series data historians SCADA DCS events alarms and tag structures
• Asset hierarchy location hierarchy measurement models and semantic standardization
• OT-to-IT integration and enterprise data alignment
• Data product design curated data layers metadata lineage and quality management
• Data governance reference data naming conventions and unit standardization
• Streaming ingestion high-volume data handling and scalable schema design
• Industrial cybersecurity awareness and secure OT data flow design
• Architecture review stakeholder collaboration coaching and technical documentation

Bachelor s Degree in Computer Science, Computer Engineering, Data Engineering, Industrial Engineering, Information Systems, or a related discipline. Master s Degree is preferred.