Data Architect

Job Code: JPC-6318 Job Title: Data Architect Location: Abu Dhabi, UAE We are looking for an experienced Data Architect to design and drive enterprise-level data architecture, data modeling, integration, and governance initiatives. The successful candidate will work closely with business and technology stakeholders to build scalable, secure, and high-performing data solutions aligned with organizational objectives. Key Responsibilities Data Architecture & Design • Design, develop, and maintain enterprise data architecture aligned with strategic business objectives. • Develop conceptual, logical, and physical data models to support enterprise data management and analytics. • Establish data architecture roadmaps ensuring scalability, security, performance, and efficiency. • Design architectures for data warehouses, data lakes, data marts, and enterprise data platforms. Data Standards & Governance • Define and enforce data architecture principles, standards, and best practices. • Establish guidelines for data modeling, data dictionaries, metadata management, and reference/master data. • Ensure architecture complies with data governance, security, privacy, and regulatory requirements. • Support implementation of Master Data Management (MDM) and data quality frameworks. Data Integration & Management • Design enterprise data integration frameworks connecting internal and external data sources. • Define and oversee ETL/ELT pipelines for extracting, transforming, processing, and loading data. • Collaborate with IT and engineering teams in selecting and implementing data management technologies. • Ensure seamless integration across enterprise applications and data platforms. Performance & Optimization • Monitor and optimize data architecture performance through testing, validation, and troubleshooting. • Improve data accessibility, security, reliability, and processing efficiency. • Ensure appropriate indexing, partitioning, and optimization techniques for improved query performance. Stakeholder & Technical Leadership • Collaborate with senior management, business stakeholders, IT teams, data engineers, analysts, and governance teams. • Translate business requirements into scalable and efficient data architecture solutions. • Provide technical guidance and architectural leadership for enterprise data initiatives. • Ensure data solutions meet both functional and strategic business requirements. Technology & Innovation • Evaluate emerging data technologies, platforms, and architecture approaches. • Conduct feasibility assessments for new data solutions and technologies. • Recommend tools and platforms that strengthen enterprise data capabilities. • Promote industry best practices in data architecture and enterprise data management. Qualifications & Experience • Bachelor s or Master s degree in Computer Science, Information Systems, Data Management, or a related discipline. • Minimum 7+ years of experience in data architecture, data modeling, and enterprise data management. • Proven experience designing and implementing data warehouses, data lakes, data marts, and enterprise data frameworks. • Strong hands-on understanding of ETL/ELT, data integration, metadata management, MDM, and data governance. • Expertise in conceptual, logical, and physical data modeling. • Strong proficiency in SQL and data modeling/architecture tools such as Erwin and ArchiMate. • Experience with cloud data platforms across Azure, AWS, and/or GCP. • Strong understanding of data security, privacy, regulatory compliance, and data quality principles. • Excellent analytical, problem-solving, communication, and stakeholder management skills. Preferred Certifications Certifications such as the following will be an advantage: • TOGAF • DAMA CDMP • AWS Certified Data Analytics or equivalent AWS data certification • Google Cloud Professional Data Engineer Show more Show less

Bachelor’s or Master’s degree in Computer Science, Information Systems, Data Management, or a related discipline. Minimum 7+ years of experience in data architecture, data modeling, and enterprise data management. Proven experience designing and implementing data warehouses, data lakes, data marts, and enterprise data frameworks. Strong hands-on understanding of ETL/ELT, data integration, metadata management, MDM, and data governance. Expertise in conceptual, logical, and physical data modeling. Strong proficiency in SQL and data modeling/architecture tools such as Erwin and ArchiMate. Experience with cloud data platforms across Azure, AWS, and/or GCP. Strong understanding of data security, privacy, regulatory compliance, and data quality principles.

Data Architecture & Design: Design, develop, and maintain enterprise data architecture aligned with strategic business objectives. Develop conceptual, logical, and physical data models to support enterprise data management and analytics. Establish data architecture roadmaps ensuring scalability, security, performance, and efficiency. Design architectures for data warehouses, data lakes, data marts, and enterprise data platforms. Data Standards & Governance: Define and enforce data architecture principles, standards, and best practices. Establish guidelines for data modeling, data dictionaries, metadata management, and reference/master data. Ensure architecture complies with data governance, security, privacy, and regulatory requirements. Support implementation of Master Data Management (MDM) and data quality frameworks. Data Integration & Management: Design enterprise data integration frameworks connecting internal and external data sources. Define and oversee ETL/ELT pipelines for extracting, transforming, processing, and loading data. Collaborate with IT and engineering teams in selecting and implementing data management technologies. Ensure seamless integration across enterprise applications and data platforms. Performance & Optimization: Monitor and optimize data architecture performance through testing, validation, and troubleshooting. Improve data accessibility, security, reliability, and processing efficiency. Ensure appropriate indexing, partitioning, and optimization techniques for improved query performance. Stakeholder & Technical Leadership: Collaborate with senior management, business stakeholders, IT teams, data engineers, analysts, and governance teams. Translate business requirements into scalable and efficient data architecture solutions. Provide technical guidance and architectural leadership for enterprise data initiatives. Ensure data solutions meet both functional and strategic business requirements. Technology & Innovation: Evaluate emerging data technologies, platforms, and architecture approaches. Conduct feasibility assessments for new data solutions and technologies. Recommend tools and platforms that strengthen enterprise data capabilities. Promote industry best practices in data architecture and enterprise data management.