Principal Engineer, Data Ma'aden Aluminium Company (MAC)

Job purpose

Lead the design, modeling, and evolution of Maaden s enterprise data architecture across both OT and IT environments. The role ensures that data products, enterprise data layers, and integration patterns are standardized, scalable, high-quality, and governed. It provides expert guidance on how diverse OT and IT data flows should be modeled, aligned, and transformed to support analytics, operations, AI/ML, and enterprise systems.

This position is a senior technical authority responsible for defining modeling standards, shaping architecture decisions, and guiding multidisciplinary teams to ensure cohesion, performance, and semantic consistency across the organization.

Key Accountabilities

• Develop conceptual, logical, and physical data models aligned with business domains, following enterprise standards and modeling principles defined in Maaden s architecture frameworks.
• Lead the creation and optimization of data product models, enterprise layer schemas, and domain-driven structures for both OT and IT sources.
• Ensure models consider technology-specific requirements, including relational, non-relational, time-series, and streaming architectures.
• Architect unified modeling approaches that address the complexities of OT environments such as remote, disconnected, and heterogeneous mining/manufacturing sites, and the differing data ingestion, latency, and operational constraints.
• Establish integration patterns ensuring consistent transformation logic, metadata, lineage, and data quality across OT IT boundaries.
• Define and maintain enterprise modeling standards, guidelines, and reusable templates to ensure consistency across the organization.
• Review and approve modeling deliverables from internal teams and external vendors.
• Mentor data modelers, engineers, and analysts to uplift enterprise modeling maturity

Skills

• Mastery of conceptual, logical, and physical data modeling.
• Expertise in data architecture frameworks, enterprise modeling principles, and metadata management.
• Understanding of OT systems (SCADA, DCS, historians, sensors) and IT data platforms.
• Ability to design data flows from edge to cloud, including ingestion, storage, curation, and consumption layers.
• Knowledge of modeling tools (Erwin, ER/Studio, Sparx EA, etc.) and lineage/governance tooling.