Senior Manager – Data & AI Architecture

Solutions+; Abu Dhabi; On-site; USD 120,000 - 180,000; Full time

Job summary

An established industry player is seeking a seasoned Data Architect to lead the enterprise-wide data architecture strategy and design. This pivotal role involves defining scalable and secure data solutions that integrate seamlessly with cloud platforms. The ideal candidate will have extensive experience in big data engineering and a strong background in data governance, ensuring compliance with industry standards. Join a forward-thinking team where you will foster a culture of innovation and data-driven decision-making, while supporting advanced analytics and AI initiatives. This is an exciting opportunity to make a significant impact in a dynamic environment.

Qualifications

• 10+ years of experience in data architecture and cloud data solutions.
• Proven expertise in Azure, AWS, and Google Cloud ecosystems.
• Strong understanding of data governance and compliance standards.

Responsibilities

• Define and implement enterprise-wide data architecture strategies.
• Lead the design of cloud-based data solutions and ensure integration.
• Foster a culture of data-driven decision-making and continuous learning.

Skills

Data Architecture

Cloud Platforms (Azure, AWS, Google Cloud)

Data Governance

Big Data Engineering

Data Modeling

ETL/ELT Processes

AI/ML Support

Data Integration

Data Quality Management

Leadership

Education

Bachelor’s Degree in Computer Science

Master’s Degree in Data Engineering

Tools

Azure Synapse

AWS Redshift

Google BigQuery

Kafka

Spark

Databricks

Power BI

Tableau

Looker

Job description

Role Description: Data Architecture Strategy & Design: • Define and implement enterprise-wide data architecture strategies, ensuring scalability, performance, and security. • Develop data models, pipelines, and storage solutions that support structured, semi-structured, and unstructured data. • Ensure alignment between data architecture, analytics, AI/ML models, and business intelligence (BI) platforms. • Drive the adoption of data lakehouse, cloud data platforms (Azure Synapse, AWS Redshift, Google BigQuery), and distributed computing frameworks. • Work closely with data engineering and analytics teams to optimize data pipelines and transformations. Cloud & Big Data Ecosystem Integration: • Lead the design and implementation of cloud-based data solutions, ensuring seamless integration with enterprise applications. • Define best practices for data ingestion, ETL/ELT, and real-time data streaming (Kafka, Spark, Databricks, etc.). • Ensure interoperability between on-premise, hybrid, and multi-cloud data environments. • Optimize data storage, processing, and retrieval across cloud platforms, improving cost efficiency and performance. Data Governance & Compliance: • Implement data governance frameworks, ensuring compliance with GDPR, HIPAA, ISO 27001, and other regulatory standards. • Define metadata management, data lineage, and data cataloging best practices. • Work with security teams to enforce data access controls, encryption, and role-based access management (RBAC). • Ensure data quality and integrity across the organization’s analytical and AI platforms. Data Integration & Interoperability: • Develop and maintain enterprise data integration frameworks, enabling smooth data exchange between systems. • Lead API-driven data integrations, event-driven architectures, and message queues for real-time data movement. • Establish data fabric and data mesh approaches, enabling a scalable, decentralized data ecosystem. • Work closely with business units, AI teams, and application developers to provide accessible, high-quality data. AI & Advanced Analytics Enablement: • Support AI and ML model development by ensuring high-quality data availability. • Define data architecture principles that optimize AI pipelines and feature engineering processes. • Work with AI engineers to deploy and operationalize AI models in cloud and edge environments. • Ensure efficient data versioning, feature stores, and reproducibility frameworks for AI workflows. Leadership & Team Development: • Lead a team of data architects, data modelers, and data integration specialists. • Foster a culture of data-driven decision-making and continuous learning. • Develop training programs and best practices for data architecture governance, performance optimization, and security. • Collaborate with cross-functional teams, including Data Science, Engineering, and Business Intelligence teams.

• Bachelor’s or master’s degree in computer science, Data Engineering, or related field. • 10+ years of experience in data architecture, big data engineering, or cloud data solutions. • Proven expertise in Azure, AWS, and/or Google Cloud-based data ecosystems (with certifications, Azure required). • Experience with data modeling tools, metadata management, and data governance platforms. • Strong understanding of data mesh, data fabric, and decentralized data architectures. • Background in leading and managing data architecture teams in enterprise environments. • Familiarity with BI/analytics tools such as Power BI, Tableau, or Looker. • Experience in supporting AI/ML workflows with structured, high-quality data pipelines