Senior Data Architect

Role - Enterprise Data ArchitectLocation- Riyadh - KSARole summary We are seeking an experienced Enterprise Data Architect to design, govern, and evolve the organization's data architecture in alignment with enterprise architecture standards (TOGAF) or other frameworks. The ideal candidate will bridge business requirements with scalable, well-governed data models across operational and analytical systems.Required skills & experience

• 8+ years of experience in data modeling, data architecture, or a related field.
• Strong knowledge of ER modeling, normalization (1NF–3NF/BCNF), and dimensional modeling.
• Practical experience with TOGAF or another enterprise architecture framework (TOGAF certification preferred).
• Experience with Master Data Management (MDM) and data governance frameworks.
• Proficiency in SQL and hands-on experience with relational databases and/or cloud data warehouses (Databricks, Snowflake, BigQuery, Redshift, etc.).
• Experience with data modeling tools (ERwin, ER/Studio, dbdiagram.io, Lucidchart, or similar).
• Familiarity with data cataloging/metadata management tools.
• Strong stakeholder communication skills — ability to translate between business language and technical models.Preferred qualifications
• TOGAF 9/10 Certification.
• Certified Databricks Expert
• Experience in Data Vault modeling.
• Experience with ETL/ELT pipelines and data integration architecture.
• Familiarity with data mesh or domain-driven data ownership models.
• Background in a regulated industry (Telecom, finance, healthcare, insurance) with strong compliance/governance needs.Key responsibilities
• Develop conceptual, logical, and physical data models aligned with business capabilities and enterprise standards.
• Understand Data Architecture activities within the TOGAF ADM, producing artifacts such as Data Entity/Business Function matrices, Application/Data (CRUD) matrices, and conceptual/logical data diagrams.
• Partner with business stakeholders to translate business processes and requirements into data domains, entities, and relationships.
• Define and enforce data governance standards: data ownership, stewardship, quality rules, and master data management (MDM) practices.
• Design dimensional models for analytics and data warehousing initiatives, and normalized models for transactional systems.
• Establish and maintain an enterprise data dictionary/glossary and metadata catalog.
• Evaluate and rationalize data flows and lineage across source systems, integration layers, and target platforms.
• Collaborate with application architects, data engineers, and BI teams to ensure models translate cleanly into physical implementations (SQL DDL, warehouse schemas, APIs).
• Assess data quality issues at the source and define remediation/standardization strategies.
• Guide architecture decisions on normalization vs. denormalization, SCD strategies, and data domain boundaries.
• Present architecture recommendations to senior stakeholders and architecture review boards.