Data Architecture & Modeling Specialist
Datamatics Technologies
Job Description: Data Architecture & Modeling Specialist
Job Title: Data Architecture & Modeling Specialist
Experience: 6–12+ Years
Location: Riyadh - Onsite
Employment Type: Full-Time
Job Overview
We are seeking an experienced Data Architecture & Modeling Specialist with 6–12+ years of experience to design, develop, and govern enterprise data architecture solutions. The ideal candidate will have strong expertise in data modeling methodologies, modern data platforms, data governance, and data integration patterns. This role requires the ability to define scalable data architectures, develop conceptual/logical/physical data models, and enable data-driven transformation initiatives across the organization.
Key Responsibilities
- Design and implement enterprise data architecture strategies aligned with business and technology objectives.
- Develop conceptual, logical, and physical data models for enterprise applications and analytical platforms.
- Create and maintain data models using industry-standard modeling tools.
- Apply data modeling methodologies including dimensional modeling and Data Vault architecture.
- Design scalable data warehouse and data lake architectures.
- Define data architecture standards, principles, and best practices.
- Collaborate with Data Engineers, BI teams, Data Scientists, and business stakeholders to deliver data solutions.
- Develop and maintain metadata, data lineage, and data governance frameworks.
- Support data platform modernization initiatives and cloud data transformation programs.
- Evaluate and recommend data technologies, tools, and architectural approaches.
- Ensure data quality, consistency, security, and compliance across enterprise data assets.
Required Technical Skills
Data Modeling & Architecture Tools
- Hands-on experience with ERwin or ER/Studio for enterprise data modeling.
- Strong understanding of conceptual, logical, and physical data modeling principles.
- Experience creating enterprise-level data models and architecture documentation.
Data Modeling Methodologies
- Strong experience with Data Vault or Kimball dimensional modeling methodologies.
- Understanding of data warehouse design patterns, star schemas, and enterprise analytics models.
Cloud & Enterprise Data Platforms
- Experience designing data architectures on BigQuery or Snowflake .
- Experience with large-scale enterprise data platforms and modern data warehouse architectures.
- Strong understanding of cloud data architecture principles.
Data Warehousing Technologies
- Experience with Teradata and enterprise-scale data warehouse environments.
- Knowledge of performance optimization, partitioning, and scalable data storage strategies.
Data Governance & Metadata Management
- Hands-on experience with Collibra or Alation for data governance, cataloging, metadata management, and data stewardship.
- Experience defining data lineage, business glossaries, and governance frameworks.
Data Integration & Change Data Capture
- Experience with CDC (Change Data Capture) tools and real-time data integration patterns.
- Understanding of data replication, streaming, and integration architectures.
Qualifications
- Bachelor's or Master's degree in Computer Science, Information Technology, Data Engineering, or a related field.
- 6–12+ years of professional experience in Data Architecture, Data Modeling, Data Warehousing, or Enterprise Data Management.
- Strong understanding of enterprise architecture principles and data strategy.
- Excellent analytical, problem-solving, and communication skills.
- Experience working with cross-functional teams in Agile environments.
Preferred Skills
- Experience designing cloud-native data architectures.
- Knowledge of modern data lakehouse architectures.
- Familiarity with data governance frameworks and regulatory requirements.
- Experience with SQL, ETL/ELT concepts, and data integration frameworks.
- Experience supporting enterprise digital transformation initiatives.
- Relevant certifications in Data Architecture, Cloud, or Data Governance are a plus.
Key Technology Stack
- Data Modeling Tools: ERwin or ER/Studio
- Modeling Methodologies: Data Vault or Kimball
- Cloud Data Platforms: BigQuery or Snowflake
- Enterprise Data Warehouse: Teradata
- Data Governance: Collibra or Alation
- Data Integration: CDC Tools
- Architecture Practices: Enterprise Data Architecture and Data Governance and Metadata Management and Data Lineage
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