Data Architect

Position Overview

Location and Work Arrangement

• The position is located in KSA and is explicitly described as onsite.

Responsibilities

• Design enterprise data architectures covering data modeling, data warehousing, and master data management.
• Design AI and machine learning systems for production environments.
• Develop and manage cloud data platforms and modern data stack architectures, including data lakes, lakehouses, and ETL/ELT pipelines.
• Design and oversee AI/ML lifecycle activities including model selection, MLOps, deployment, and monitoring.
• Architect LLM and generative AI solutions including RAG pipelines, vector databases, prompt engineering, and model orchestration.
• Translate business requirements into technical architecture.
• Communicate with engineering teams and executive stakeholders.
• Design APIs and system integrations for interconnected platforms and systems.
• Ensure alignment with data governance and compliance frameworks.
• Support smart-city, government, and enterprise platform initiatives involving multiple stakeholders and integrated systems.

Must-Have Experience

• At least 8 years of experience in data architecture, including 2–3 or more years designing AI/ML systems in production.
• Strong hands-on experience with Azure, AWS, or GCP and modern data stacks including data lakes, lakehouses, and ETL/ELT pipelines.
• Proven experience designing enterprise data architectures covering data modeling, data warehousing, and master data management.
• Solid understanding of the AI/ML lifecycle, including model selection, MLOps, deployment, and monitoring.
• Experience with LLM and generative AI architecture, including RAG pipelines, vector databases, prompt engineering, and model orchestration.
• Experience with data governance and compliance frameworks.
• Ability to translate business requirements into technical architecture and communicate with engineering teams and executive stakeholders.
• Experience with API design and system integration.

Technical Skills

• Data engineering and data architecture skills should range from moderate to advanced.
• AI engineering skills should range from basic to intermediate.
• Strong SQL skills are required.
• At least one programming language is required, with Python identified as the common example.

Good-to-Have Qualifications

• Direct experience with PDPL, NCA ECC, NDMO, GDPR, HIPAA, or similar frameworks is advantageous.
• Familiarity with real-time or streaming data architectures, Kafka, or event-driven systems is advantageous.
• Experience with IoT data ingestion is advantageous.
• Enterprise architecture certifications such as TOGAF or cloud architect certifications are advantageous.
• Government, smart-city, or public-sector platform experience is advantageous.
• Experience in vendor or multi-stakeholder environments is advantageous.

Language Skills

• English language skills are preferred.
• Arabic language skills are an advantage.