Data Architect

EJADA; Riyadh; On-site; SAR 280,000 - 520,000; Full time

Job summary

EJADA is seeking a Data Architect & Modeler Consultant in Riyadh to design, govern, and maintain enterprise data architectures and models that drive analytics, AI, and data-driven initiatives.

The role translates business needs into conceptual, logical, and physical data models, ensures governance, scalability, and data quality, and collaborates with stakeholders to deliver implementation-ready artifacts across data warehouses, lakes, and analytical platforms.

Qualifications

• Bachelor's degree or higher in a relevant field.
• Professional certifications in Data Architecture, Data Modeling, Data Management, or Enterprise Data Management.
• CDMP (Certified Data Management Professional) or equivalent certification.
• 6+ years in Data Architecture, Data Modeling, Data Design, Data Engineering, or Enterprise Data Management.
• Proven experience designing enterprise data platforms and analytical environments.
• Experience with large-scale data transformation, analytics, and AI initiatives.

Responsibilities

• Design and govern enterprise data architecture frameworks aligned with business and technology strategies.
• Identify and define the key components of the enterprise data landscape.
• Design end-to-end data platform architectures supporting analytics, AI, reporting, and operational use cases.
• Develop and maintain conceptual, logical, and physical data models.
• Ensure data models align with business semantics, performance requirements, scalability, and data quality standards.
• Design scalable and modular data architectures to support current and future business needs.
• Collaborate with business stakeholders to translate business objectives into data requirements, business rules, and transformation logic.
• Define source-to-target mappings and data transformation specifications.
• Perform source system analysis and identify extraction, integration, and ingestion requirements.
• Design data flows across data warehouses, data lakes, lakehouses, and analytical platforms.
• Support the definition of data integration approaches and data movement strategies.
• Prepare high-level and detailed solution design documents, architecture artifacts, and modeling deliverables.
• Work closely with data architects, data analysts, data engineers, and implementation teams to ensure successful solution delivery.
• Ensure compliance with data governance standards, metadata requirements, lineage principles, and enterprise architecture guidelines.
• Support continuous improvement initiatives related to data architecture, modeling standards, and design methodologies.

Skills

Data warehouse architecture

Data lake architecture

Lakehouse architecture

Data modeling

Data flow design

Conceptual data modeling

Logical data modeling

Physical data modeling

Dimensional modeling

Master data modeling

Reference data modeling

SCD (Slowly Changing Dimensions)

Data governance

Data lineage

Data quality requirements

Business requirements analysis

Source-to-target mapping

Education

Bachelor's Degree in Computer Science, Information Technology, Engineering, Information Systems, Data Science

Job description

The Data Architect & Modeler Consultant is responsible for designing, governing, and maintaining enterprise data architectures and data models that support analytics, reporting, AI, and data-driven business initiatives. The role ensures that data structures are scalable, integrated, governed, and aligned with business requirements while translating business needs into conceptual, logical, and physical data models, integration patterns, and implementation-ready design artifacts.

Key Accountabilities:

• Design and govern enterprise data architecture frameworks aligned with business and technology strategies.
• Identify and define the key components of the enterprise data landscape.
• Design end-to-end data platform architectures supporting analytics, AI, reporting, and operational use cases.
• Develop and maintain conceptual, logical, and physical data models.
• Ensure data models align with business semantics, performance requirements, scalability, and data quality standards.
• Design scalable and modular data architectures to support current and future business needs.
• Collaborate with business stakeholders to translate business objectives into data requirements, business rules, and transformation logic.
• Define source-to-target mappings and data transformation specifications.
• Perform source system analysis and identify extraction, integration, and ingestion requirements.
• Design data flows across data warehouses, data lakes, lakehouses, and analytical platforms.
• Support the definition of data integration approaches and data movement strategies.
• Prepare high-level and detailed solution design documents, architecture artifacts, and modeling deliverables.
• Work closely with data architects, data analysts, data engineers, and implementation teams to ensure successful solution delivery.
• Ensure compliance with data governance standards, metadata requirements, lineage principles, and enterprise architecture guidelines.
• Support continuous improvement initiatives related to data architecture, modeling standards, and design methodologies.

Minimum Qualifications:

• Bachelor's Degree in Computer Science, Information Technology, Engineering, Information Systems, Data Science.
• Professional certifications in Data Architecture, Data Modeling, Data Management, or Enterprise Data Management.
• CDMP (Certified Data Management Professional) or equivalent certification.
• +6 years of experience in Data Architecture, Data Modeling, Data Design, Data Engineering, or Enterprise Data Management.
• Proven experience designing enterprise data platforms and analytical environments.
• Experience working with large-scale data transformation, analytics, and AI initiatives.

Job-Specific Skills:

• Data Warehouse Architecture.
• Data Lake Architecture.
• Lakehouse Architecture.
• Data Flow Design.
• Conceptual Data Modeling.
• Logical Data Modeling.
• Physical Data Modeling.
• Dimensional Modeling (Facts & Dimensions).
• Master Data Modeling.
• Reference Data Modeling.
• Normalization and Denormalization Techniques.
• Slowly Changing Dimensions (SCD).
• Business Requirements Analysis.
• Source System Analysis.
• Data Mapping and Transformation Design.
• Source-to-Target Mapping.
• Data Extraction Design.
• Data Integration Design.
• Detailed Design Specifications.
• Data Governance Principles.
• Data Lineage and Traceability.
• Data Quality Requirements.
• Data Standards and Business Definitions.