Data Architecture Manager

About GIG Gulf

GIG Gulf (a Fairfax company) is part of the Gulf Insurance Group (GIG), the #1 largest regional composite insurer in the Middle East and North Africa, with a presence in 12 markets. GIG Gulf is an ‘A’ rated regional insurer with a top 5 position in each of its markets (UAE, Oman, Qatar, Bahrain). With over 70 years in the region, GIG Gulf offers a wide range of insurance products and services for corporates, SMEs, and individual customers. The company emphasizes Regional Growth, Customer Experience, and Digital Transformation, fostering a diverse and inclusive working environment with over 800 employees from 60+ nationalities.

Job Purpose

The Data Architecture Manager will contribute to the business purpose of a Regional Insurance Leader by being a data-driven, technologically savvy, and hands-on Data Architect with Data Engineering exposure on AWS and Azure Cloud. You will express your passion with GIG Gulf business and IT stakeholders to:

• Define and maintain GIG Gulf IT Data standards, architectural guidelines, and solutions.
• Lead pilots, POCs, and exploration of new innovative solutions, practices, and patterns.
• Influence the delivery of GIG Gulf Data & AI projects on time, quality, and budget.
• Actively contribute to GIG Gulf’s Data & AI vision and roadmap, including business case definition, project requirements, organization, and methodology.

Key Responsibilities

Architecture

• Lead the definition and maintenance of GIG Gulf’s enterprise data and AI architecture and delivery roadmap.
• Drive the data and AI architecture aligned with GIG Gulf’s business and technology strategy.
• Contribute to the IT Strategy Plan, including cloud, data, analytics, and AI capabilities.
• Support the selection and evolution of data and AI platforms, technologies, and strategic partners.

Data & AI Platform Leadership

• Define architectural patterns for data platforms supporting analytics, reporting, AI/ML, and GenAI use cases.
• Guide the design of AI-ready data foundations, including structured and unstructured data pipelines.
• Ensure architectural consistency, reuse, and alignment across data, analytics, and AI solutions.
• Work closely with information security, risk, and compliance teams to embed governance and controls.

Technical Leadership

Strong technical leader with broad and in-depth understanding of:

• Data architecture, data modeling, and data governance.
• Data engineering and cloud-native data platforms.
• Analytics, BI, and AI/ML solution patterns.
• Generative AI concepts including LLM-based solutions, retrieval-augmented generation (RAG), and vector-based retrieval architectures.
• Maintain practical knowledge of data and AI services from AWS and Azure along with modern development practices.

Operational & Technical Responsibilities

Data & AI Architecture

Function as an active, initiative‑taking Data and AI Architect for GIG Gulf initiatives:

• Refine and maintain data and AI architecture frameworks, guidelines, and design patterns.
• Define target-state architectures for master data (customer, product, provider, referential data).
• Contribute to solution and technical architecture covering:
  • Data lakes and analytical platforms.
  • AI/ML and GenAI-enabled use cases.
• Design architecture that supports AI workloads, including (desirable):
  • Retrieval-augmented generation (RAG) patterns.
  • Vector storage and semantic retrieval for enterprise knowledge use cases.
  • Secure integration of public or foundation models with internal data.

Tangible Outcomes & Delivery Focus

Maintain a strong delivery and results orientation:

• Contribute to the data and AI roadmap aligned to business priorities.
• Lead implementation of data and analytics solutions on AWS (e.g., S3, Glue, Redshift, RDS, Lambda, Athena) and/or Azure (e.g., Data Lake Storage, Data Factory, Synapse Analytics, Azure Functions, Event Hubs).
• Oversee data modeling for OLTP and OLAP systems, including data quality, cleansing, and de-duplication initiatives.
• Guide data engineering practices using Spark (Python, Spark SQL), data workflows, and automated pipelines.
• Support AI-enabled analytics and reporting use cases through curated data marts and BI extensions.
• Ensure solutions are production-ready, documented, and maintainable.

AI Solution Governance & Integration

• Define architectural guardrails for enterprise AI usage, including (desirable):
  • Responsible and compliant use of LLMs and GenAI services.
  • Data access, privacy, and residency controls for AI solutions.
  • Integration patterns for AI agents and automated workflows where applicable.
• Support evaluation and controlled adoption of AI technologies, avoiding fragmented or unmanaged deployments.
• Ensure AI solutions are aligned with enterprise architecture, security, and regulatory requirements.

Communication & Stakeholder Engagement

• Prepare clear, structured architectural proposals and decision papers with supporting rationale.
• Communicate architectural choices to both technical and non-technical stakeholders.
• Provide clear recommendations aligned with business outcomes and strategy.
• Promote collaboration, reuse, and shared ownership across delivery teams.

Quality & Operational Excellence

• Ensure high-quality testing, data validation, and operational readiness of data and AI platforms.
• Support incident, problem, and defect analysis related to data and AI solutions.
• Track and follow up on issues to ensure timely resolution and continuous improvement.

People Leadership

• Manage recruitment and onboarding of data and AI team members in collaboration with HR.
• Set, review, and track team objectives and performance.
• Support team development through coaching, mentoring, and targeted training.
• Foster a collaborative culture aligned with GIG values and delivery commitments.

Business / Domain Knowledge Requirements

• Knowledge of Health Data industry.
• Basic knowledge of the insurance business.
• Basic understanding of market practices/business processes.
• Understanding of regulatory challenges, including compliance, data privacy and residency.

Minimum Requirements

Qualifications & Technical Skills

• Bachelor’s degree in computer science, Information Technology, Engineering, or a related technical discipline.
• Master’s degree or relevant professional certifications.