Data Engineer

Organizational Context

The United Nations Economic and Social Commission for Western Asia (ESCWA) supports member states in advancing economic and social development through data and analytics. The Decision-Support and Data Science Division (DS&DSD) develops advanced data platforms and AI systems. This role supports the development of a Labour Market Information System (LMIS) for Qatar.

Job Purpose

This Data Engineer role is crucial for the technical development, integration, and operationalization of the Qatar Labour Market Information System (LMIS). The purpose is to build and maintain robust data pipelines and architectures, ensuring the LMIS effectively integrates various data sources. The role contributes to providing timely, granular, and actionable insights on labor market dynamics, supporting national policymaking. The Data Engineer will collaborate with internal teams and national counterparts to deliver a high-quality, data-driven platform that enhances the availability and analytical use of labor market data.

Responsibilities

Design, build, and maintain ETL/ELT data pipelines. Automate data ingestion from diverse sources including databases, APIs, and streaming services. Implement rigorous data validation and quality checks to ensure data integrity. Utilize cloud platforms like Azure for developing data solutions. Collaborate with Data Scientists and Full Stack Web Developers to deliver clean and reliable data. Create and maintain comprehensive technical documentation, including user manuals, training materials, and functional specifications. Provide ongoing support for deployed pipelines, managing version control, data recovery, and deployment strategies. Research and evaluate emerging technologies and industry trends to enhance data system capabilities.

Work Experience

A minimum of 5 years of professional experience is required, specifically with Python, SQL, cloud environments, container orchestration (Kubernetes), and DevOps automation. Experience in database design and development using MS SQL Relational Database is also necessary. Familiarity with semantic modeling, knowledge graphs, and AI/ML integration for data systems is desirable.

Skills

Python, SQL, Cloud Environments (Azure), Container Orchestration (Kubernetes), DevOps Automation, Database Design, MS SQL Relational Database, ETL/ELT Pipeline Development, Data Ingestion Automation, Data Validation, Technical Documentation, Problem-Solving, Communication.

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