Senior Enterprise Data Modeling & Architecture Lead

Ma'aden Aluminium Company (MAC); Medina; On-site; SAR 350,000 - 650,000; Full time

Job summary

Ma'aden Aluminium Company (MAC) seeks a senior data architect to lead the design modeling and evolution of enterprise data architecture, ensuring standardized, scalable, high-quality data products across domains.

You will define canonical models, conformed dimensions, curated layer schemas, and governance processes, partnering with data governance and engineering teams to enable trusted analytics, AI enablement, and cross-domain interoperability.

Qualifications

• Bachelor’s or higher in CS/IS/Analytics with extensive data modeling experience.
• 10–15 years in data modeling, data architecture, and enterprise information architecture.
• Experience defining modeling standards, metadata, lineage, governance controls and quality assurance.
• Ability to design canonical models, conformed dimensions, and reusable data patterns.

Responsibilities

• Lead enterprise data modeling across conceptual, logical, and physical layers.
• Define canonical models, conformed dimensions, master reference data, and reusable patterns.
• Design data product schemas and curated layer schemas for analytics, AI use cases, and downstream integrations.
• Establish architecture standards and governance with data governance teams and stakeholders.
• Mentor data modelers and review modeling deliverables to ensure consistency and quality.

Skills

Data modeling

Data architecture

Canonical models

Dimensional modeling

Metadata governance

Education

Bachelor's degree in related field

Master’s degree preferred

Tools

Relational databases

NoSQL databases

Time-series databases

Lakehouse/Warehouse

ETL/ELT pipelines

Job description

Ma'aden Aluminium Company (MAC) seeks a senior data architect to lead the design modeling and evolution of enterprise data architecture, ensuring standardized, scalable, high-quality data products across domains.

You will define canonical models, conformed dimensions, curated layer schemas, and governance processes, partnering with data governance and engineering teams to enable trusted analytics, AI enablement, and cross-domain interoperability.