Data Architect

Position summary

Location and duration

• The posting lists Dubai, UAE, and considers candidates currently working in the UAE.
• Full-time employment; the stated duration is one year, extendable.

Candidate requirements

• Bachelor's degree minimum.
• 10+ years of experience in Data Architecture, Data Warehousing, or Enterprise Data Management.
• Proven experience designing and leading enterprise-scale Data Warehouse, Data Lake, and Lakehouse programs.
• Strong expertise in enterprise data architecture, data modeling, and architecture governance.
• Hands-on cloud and hybrid data platform design using Microsoft Azure data services, including Microsoft Fabric, Azure Data Lake, Synapse Analytics, and Azure SQL.
• Experience with data integration, ETL/ELT, and Change Data Capture (CDC).
• Experience with SQL-based platforms such as SQL Server, Oracle, or PostgreSQL.
• Experience implementing data governance, metadata management, and data quality frameworks.
• Understanding of enterprise reporting, analytics, and business intelligence architectures.
• Ability to influence senior stakeholders and lead cross-functional teams and large-scale initiatives.

Architecture and platform responsibilities

• Define enterprise data architecture standards, principles, and target-state roadmaps.
• Design scalable, secure platforms for reporting, analytics, business intelligence, and AI use cases.
• Develop conceptual, logical, and physical data models for enterprise data domains.
• Establish architecture governance aligned with enterprise architecture standards.
• Lead design and delivery of Enterprise Data Warehouse, Data Lake, and Lakehouse initiatives.
• Define integration, modeling, and analytics strategies for structured and unstructured datasets.
• Design dimensional models, semantic layers, and reporting architectures for analytics and executive dashboards.
• Support a single source of truth through data quality and master data management practices.
• Design hybrid cloud and on-premises architectures and migration strategies from legacy platforms.
• Architect data ingestion, integration, and real-time analytics solutions.

Governance and leadership responsibilities

• Define data governance frameworks and stewardship processes.
• Set standards for data classification, metadata, retention, lineage, and quality, and design controls to protect sensitive and regulated data.
• Translate business and technology requirements into architecture solutions.
• Provide architectural leadership to data engineering, analytics, and project delivery teams.
• Lead architecture reviews, design workshops, and governance forums.
• Mentor data engineers, analysts, and junior architects.

Additional experience welcomed

• Data cataloging, data lineage, and Master Data Management solutions.
• Data retention and lifecycle management frameworks.
• Data streaming and real-time analytics architectures.
• API-led integration patterns and modern integration frameworks.
• Data privacy, PII protection, encryption, data masking, tokenization, and access control solutions.
• Government, telecom, transportation, banking, or large enterprise data programs.
• AI/ML and Generative AI use cases on enterprise data platforms.
• Data Mesh or domain-oriented data architectures.
• Sovereign cloud, regulatory compliance, and data residency requirements.