BACKGROUND INFORMATION

Under the operational guidance of the Head of the Future Networks & Spectrum Management (Access) Division (FNS) within the Digital Networks & Environment Department (DNE), and in close collaboration with the division's team members, the role of this consultancy is to ensure the support of successful implementation of infrastructure projects and toolset and provide technical assistance to build and scale a web-based application with security built in at every layer. The full stack engineer consultant will design, develop, and maintain frontend, backend, and data workflows while ensuring user datasets are handled securely, compliantly, and with auditable controls.

TERMS OF REFERENCE

The consultant will:

• Build and maintain frontend and backend features with secure data interactions.
• Develop scalable FastAPI services for data ingestion, transformation, and delivery.
• Implement reliable, secure data workflows in Python and Databricks.
• Apply best practices (input validation, API authentication, secure session handling).
• Prevent common vulnerabilities.
• Design APIs and services with robust access control and abuse prevention.
• Implement secure storage patterns.
• Harden compute and data pipelines in Databricks.
• Implement authentication/authorization flows.
• Manage user and service-level roles across the application.
• Enhance CI/CD pipelines with automated testing, code quality checks, and security scans.

CONCRETE DELIVERABLES

• Development and maintenance of secure, production-grade frontend and backend features.
• Implementation of documented APIs with integrated authentication and authorization.
• Development of data ingestion, processing, and output pipelines.
• Enhancement of automated tests and CI/CD checks covering both functionality and security.
• Integration of logging, monitoring, and alerting into deployed services.
• Submission of a well-structured documentation for code, workflows, and operational handoffs.

COMPETENCIES

• Proficiency in Python for data analysis and machine learning.
• Advanced knowledge of data processing tools and libraries such as pandas and numpy.
• Experience with SQL and NoSQL databases, including PostgreSQL and MongoDB.
• Strong understanding of statistical methods and their application in data analysis.
• Familiarity with machine learning frameworks and libraries such as scikit-learn, TensorFlow, scikit-learn and PyTorch.
• Proficiency in visualization tools like Matplotlib, Seaborn, Plotly, and Tableau.
• Familiarity with big data tools and platforms such as Hadoop, Spark, and Kafka.
• Knowledge of geospatial libraries and tools like geopandas, shapely and QGIS.
• Experience with cloud platforms such as AWS, Azure, and Google Cloud for data storage and processing.
• Proficiency in version control systems like Git and platforms such as GitHub and GitLab.
• Ability to develop, train, and evaluate machine learning models.
• Ability to communicate complex data insights effectively to both technical and non-technical stakeholders.

QUALIFICATIONS REQUIRED

Education:

Advanced university degree in computer science, data science, data engineering, telecommunications, or a related field OR education from a reputed college of advanced education with a diploma of equivalent standard to that of an advanced university degree in one of the fields above.

Experience:

At least five (5) years of demonstrated experience with a specific focus on designing and implementing automated data pipelines. Technical knowledge in:

• Python, SQL, Git, PostgreSQL, Microsoft Azure, Amazon Web Services, Docker, Kubernetes, Apache Airflow, etc.
• Frontend Development in JavaScript, TypeScript.
• Backend Development in Python (FastAPI). API design.
• Python pipelines, Databricks workflows, ETL security.
• Cloud (AWS).
• OAuth2, OIDC, JWT, role-based design.
• DevOps/CI/CD (GitHub, AzureDevops or similar).

Languages:

Knowledge of English at advanced level. Knowledge of another official language of the Union (Arabic, Chinese, French, Russian, Spanish) would be an advantage.

REMUNERATION INFORMATION

Between USD 230 and USD 420 per working day to be defined according to the work experience of the consultant and the complexity of the assignment.