Data Architect

 Data Architecture Development:

• Design and maintain data architecture frameworks, including conceptual, logical, and physical data models.
• Develop and enforce data standards, policies, and governance frameworks to ensure data quality, consistency, and security.
• Lead the design and implementation of data integration pipelines, ensuring seamless interoperability between internal and external systems.

2. Data Discovery and Profiling:

• Conduct data discovery and profiling activities to assess data quality, identify anomalies, and understand data relationships.
• Analyze existing data assets and processes to identify opportunities for optimization and improvement.
• Collaborate with stakeholders to document data requirements and identify data sources.

3. Data Integration and Transformation:

• Develop and implement ETL (Extract, Transform, Load) processes to integrate data from multiple sources.
• Ensure the integrity, accuracy, and timeliness of data flowing through pipelines.
• Design and implement data lakes, data warehouses, and data marts to support analytics and reporting needs.

4. Data Governance and Compliance:

• Establish and enforce governance practices to ensure compliance with organizational policies and regulatory requirements.
• Monitor and manage data security, privacy, and access controls to protect sensitive information.
• Provide expertise in regulatory standards such as Qatar NIA, GDPR, HIPAA, or equivalent as applicable.

5. Analytics and AI Enablement:

• Support the development of AI-driven use cases by designing data pipelines and models optimized for machine learning and analytics.
• Collaborate with data scientists and business analysts to enable predictive analytics and advanced data insights.
• Leverage cloud-based data services and platforms to enhance scalability and efficiency.

6. Collaboration and Stakeholder Engagement:

• Work closely with business units, application architects, and IT teams to align data architecture with organizational goals.
• Partner with cross-functional teams to ensure data solutions meet performance, scalability, and security requirements.
• Act as a liaison between technical teams and business stakeholders to translate business needs into technical data solutions.

7. Emerging Technologies and Innovation:

• Stay updated on emerging trends in data architecture, big data, and analytics technologies.
• Evaluate and recommend tools and technologies that enhance the organization’s data capabilities.
• Promote a culture of innovation by identifying opportunities to use data in transformative ways.

8. Documentation and Knowledge Sharing:

• Create and maintain comprehensive documentation for data architecture, models, and processes.
• Provide training and guidance to teams on best practices for data management and governance.
• Develop dashboards and reports to communicate data architecture performance and compliance metrics to stakeholders.