Data Modeler & Architect

National Bank of Kuwait; Jeddah; On-site; SAR 200,000 - 300,000; Full time

Job summary

A leading banking institution in Jeddah seeks a Data Modeler & Architect responsible for designing and developing the bank’s enterprise data architecture. The role involves collaborating with stakeholders to enforce data standards and implement secure data solutions. Candidates must have at least 7 years of experience in data modeling, strong expertise in ER modeling, and proficiency with industry-standard tools. This role requires solid understanding of data governance and local regulatory standards.

Qualifications

• Minimum 7 years of proven experience in data modeling within large-scale enterprise environments.
• Strong expertise in ER modeling, dimensional modeling, and data warehousing concepts.
• Comprehensive knowledge of SAMA regulations and NDMO data standards.

Responsibilities

• Define, develop and maintain conceptual, logical, and physical data models aligned with business and regulatory requirements.
• Establish data architecture principles, standards, and best practices across the bank.
• Collaborate closely with Data Governance, Data Engineers, IT, and Business teams to ensure high-quality data design.

Skills

Data modeling (conceptual, logical, physical)

Data architecture design

Database design & optimization

SQL (advanced querying & performance tuning)

ETL/ELT development

Data warehouse, data lake design

Metadata management & data cataloging

Master data management (MDM)

Data quality and validation frameworks

Data integration patterns (batch, streaming, APIs)

Data governance implementation

Data lineage and impact analysis

Modeling tools (ERwin, PowerDesigner, SQL DBM, etc.)

Tools

ERwin

PowerDesigner

Job description

Job Purpose

The Data Modeler & Architect is responsible for designing, developing, the bank’s enterprise data architecture and data models to support operational systems, analytics, and strategic decision-making. Partners with business stakeholders, data engineers, and technology team to translate business requirements into robust data designs, establish and enforce data standards, and guide the implementation of secure, high-quality, and maintainable data solutions.

Key Responsibilities & Accountabilities

• Define, develop and maintain conceptual, logical, and physical data models aligned with business and regulatory requirements.
• Establish data architecture principles, standards, and best practices across the bank.
• Provide architectural guidance for data platforms, data integration solutions, and analytics environments
• Collaborate closely with Data Governance, Data Engineers, IT, and Business teams to ensure high-quality data design and delivery.
• Implement data modeling best practices and contribute to enterprise data standards.
• Support data warehousing, metadata management, and data quality improvement initiatives.
• Translate complex business needs into robust and scalable data structures.
• Evaluate and recommend data management technologies, tools, and frameworks.

Qualification & Experience

• Minimum 7 years of proven experience in data modeling within large-scale enterprise environments.
• Strong expertise in ER modeling, dimensional modeling, and data warehousing concepts.
• Proficiency with industry-standard modeling tools (e.g., ERwin, PowerDesigner, or equivalent).
• Solid understanding of data governance frameworks, data architecture, and regulatory data requirements.
• Comprehensive knowledge of SAMA regulations and NDMO data standards, with ability to model data in line with local regulatory expectations.
• Proven experience in the banking or financial services sector is required.
• Excellent analytical and communication skills.

Competencies

• Enterprise Data Architecture – Ability to design, implement, and maintain scalable enterprise data architectures across operational, analytical, cloud, and hybrid environments.
• Data Modeling Mastery – Expertise in conceptual, logical, and physical data modeling using industry-standard tools and best practices.
• Database & Storage Systems – Strong knowledge of relational, NoSQL, and cloud-native databases and the ability to optimize structures for performance and scalability.
• Data Integration & Pipelines – Skilled in ETL/ELT design, data pipeline orchestration, and integration patterns used in modern data platforms.
• Cloud & Modern Data Platforms – Proficient with cloud ecosystems (AWS, Azure, GCP), data lakes, and data warehouse technologies.
• Data Governance & Quality – Solid understanding of metadata, lineage, MDM, data quality controls, and standardization frameworks.
• Security & Compliance – Knowledge of data privacy, security protocols, and regulatory compliance requirements (NDMO, PDPL).

Skills

• Data modeling (conceptual, logical, physical)
• Data architecture design
• Database design & optimization
• SQL (advanced querying & performance tuning)
• ETL/ELT development
• Data warehouse, data lake design
• Metadata management & data cataloging
• Master data management (MDM)
• Data quality and validation frameworks
• Data integration patterns (batch, streaming, APIs)
• Data governance implementation
• Data lineage and impact analysis
• Modeling tools (ERwin, PowerDesigner, SQL DBM, etc.)