Data Engineer; Arabic

Data Engineer – Population Modeling

Role Overview:

The Data Engineer will design, build, and maintain scalable data pipelines and platforms that support population modeling and demographic analysis for evidence-based national planning. The role ensures the availability, quality, security, and governance of data used by data scientists and policy analysts to produce reliable forecasts and insights.

• Design, develop, and maintain robust ETL/ELT pipelines integrating demographic, census, and national accounts data.
• Build and optimize batch and real-time data pipelines for large-scale population and macroeconomic datasets.
• Implement data quality frameworks, logging, lineage, and security controls to ensure accuracy, traceability, and compliance.
• Collaborate closely with modelers and analysts to translate population modeling requirements into well-structured, analytics-ready datasets.
• Manage and optimize relational and non-relational databases supporting demographic and foresight models.
• Support production environments by monitoring pipelines, resolving data issues, and ensuring system reliability.
• Develop and deploy data models, APIs, and visualizations to improve accessibility and usability across the foresight department.
• Maintain comprehensive documentation, version control, and CI/CD pipelines aligned with data governance standards.
• Ensure effective knowledge transfer and documentation of methodologies, assumptions, and analytical outputs.

• Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related field.
• 4+ years of hands‑on experience in data engineering, ETL development, or database management.
• Demonstrated experience with population modeling techniques and demographic data analysis.
• Experience working with government entities, public sector organizations, think tanks, or international institutions is strongly preferred.

• Strong proficiency in SQL and Python for data engineering and transformation.
• Hands‑on experience with cloud data platforms such as AWS, Azure, or GCP (data lakes, warehouses, orchestration tools).
• Experience with CI/CD pipelines, version control systems (e.g., Git), and data security protocols.
• Familiarity with data APIs, data modeling, and analytics enablement frameworks.
• Strong proficiency in Microsoft Office, especially for reporting and documentation.

• Fluency in Arabic and English, both written and spoken.

• Strong analytical and critical thinking capabilities.
• High attention to detail with a strong commitment to data quality and research rigor.
• Ability to collaborate effectively across multidisciplinary and policy-focused teams.
• Skilled at translating complex analytical outputs into clear, actionable insights for decision-makers.
• Curious, innovative, and adaptable, with a strong interest in emerging data and modeling technologies