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Data Solutions Architect

📅 Apr 29
Data ArchitectureData GovernanceAI And Machine Learning PlatformsData Integration

📜 Description

  • Design and implement enterprise-level data architecture frameworks (e.g., data lake, data warehouse, data mesh).
  • Define and enforce data governance, security, and compliance standards across the organization.
  • Lead the architecture of AI and machine learning platforms and enterprise data products.
  • Collaborate closely with business, technology, and risk teams to align data capabilities with strategic priorities.
  • Drive adoption of modern data paradigms such as Data Mesh and Data Product-based architectures.

🛠️ Requirements

  • 8–10+ years of experience in data architecture, data platforms, or enterprise data transformation.
  • Experience leading enterprise data transformation initiatives in banks, financial institutions, or NBFC environments.
  • Strong stakeholder management skills at executive and leadership levels.
  • Demonstrated ability to drive organization-wide adoption of data strategy and architecture frameworks.
  • Experience working in complex, regulated, or multi-country environments.
Full job description

AI & Data Center of Excellence – Abu Dhabi, UAE

Role Overview

As a Data Solutions Architect, you will define, design, and govern enterprise-wide data architecture to ensure alignment with business strategy, regulatory requirements, and long-term scalability needs.

This is a strategic leadership role that requires deep expertise in financial data ecosystems and enterprise transformation initiatives. You will play a critical role in shaping the organization’s data strategy, enabling advanced analytics, AI-driven decision-making, and regulatory compliance across multiple business domains.

Experience Requirement

• Senior Level Only: 8–10+ years of experience in data architecture, data platforms, or enterprise data transformation

Key Responsibilities

• Design and implement enterprise-level data architecture frameworks (e.g., data lake, data warehouse, data mesh)
• Define and enforce data governance, security, and compliance standards across the organization
• Lead the architecture of AI and machine learning platforms and enterprise data products
• Collaborate closely with business, technology, and risk teams to align data capabilities with strategic priorities
• Ensure compliance with regulatory frameworks (e.g., GDPR and local financial regulations)
• Drive adoption of modern data paradigms such as Data Mesh and Data Product-based architectures
• Establish best practices for data integration, scalability, performance, and reliability
• Guide enterprise data transformation programs and modernization initiatives

Financial Services Expertise (Mandatory)

Candidates must demonstrate hands-on experience in financial data environments, including:

• Regulatory reporting and compliance-driven data architectures
• Risk and finance data platforms
• Customer and transaction data models
• Data governance frameworks aligned with regulatory requirements

Technical Expertise

Cloud Platforms
• AWS
• Azure
• Google Cloud Platform (GCP)

Data Architecture & Modelling
• Enterprise data modelling frameworks (e.g., Kimball, Data Vault)
• Data warehouse and data lake architectures
• Data integration and distributed data systems

Databases & Data Technologies
• Relational databases
• NoSQL databases
• Graph databases
• Vector databases

Data & AI Platforms
• API-driven data ecosystems
• MLOps and AI platform architecture
• Scalable data infrastructure design

Evaluation Criteria

Candidates will be evaluated based on:

• Proven experience delivering enterprise-scale data architecture solutions
• Ability to align business strategy with data and analytics strategy
• Experience leading large-scale data transformation or modernization programs
• Leadership capabilities and stakeholder influence across technical and business teams
• Track record of implementing governance, compliance, and scalable data frameworks

Key Performance Indicators (KPIs)

• Scalability, reliability, and performance of enterprise data platforms
• Compliance with governance and regulatory requirements
• Adoption of enterprise data architecture standards across business units
• Reduction of data silos and improvement in data accessibility and consistency
• Enablement of advanced analytics and AI capabilities across the organization

Preferred Profile

• Experience leading enterprise data transformation initiatives in banks, financial institutions, or NBFC environments
• Strong stakeholder management skills at executive and leadership levels
• Demonstrated ability to drive organization-wide adoption of data strategy and architecture frameworks
• Experience working in complex, regulated, or multi-country environments
• Strategic mindset with strong decision-making and communication skills

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