Job Description
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.
