Junior Data Engineer
Organizational Context
The Decision-Support and Data Science Division (DSDSD) within ESCWA drives modernization and innovation through advanced analytics and decision-support services for UN entities and Member States. Aligned with the UN 2.0 agenda, DSDSD utilizes data-driven insights and emerging technologies to inform policymaking and operations, supporting sustainable development.
Job Purpose
This role supports ESCWA's data platforms and digital initiatives by developing, enhancing, and maintaining data engineering solutions and automated data collection processes. The Junior Data Engineer will create and manage ETL/ELT pipelines, web scraping solutions, and data ingestion from various sources. Key contributions include ensuring data accuracy, reliability, and supporting evidence-based decision-making through robust data infrastructure. The position also involves preparing technical and user documentation to ensure the effective implementation and sustainability of developed solutions, aligning with UN standards and best practices.
Responsibilities
Design, develop, and maintain ETL/ELT pipelines for automated data collection, transformation, and integration. Develop and maintain web scraping and data extraction solutions for structured and unstructured data from diverse sources. Automate data ingestion from multiple sources including websites, APIs, databases, and files. Implement data validation, cleansing, quality checks, and monitoring mechanisms to ensure data accuracy and reliability. Develop resilient scraping processes to handle source website changes. Provide ongoing support and maintenance for deployed data pipelines and web scrapers, including troubleshooting, version control, monitoring, data recovery, and deployment management. Prepare and update project-based technical documentation, user documentation, and functional specifications.
Work Experience
A minimum of 1 year of professional hands-on experience with Python is required. Demonstrated experience in designing, developing, and maintaining web scraping and automated web data extraction solutions is essential. Experience with data validation, transformation, quality assurance, monitoring, and troubleshooting of automated data pipelines is required. Knowledge of database design and development using MS SQL Relational Database is also required.
Skills
Python, Web Scraping, Data Extraction, ETL/ELT Pipeline Development, Data Ingestion, Data Validation, Data Transformation, Data Quality Assurance, Database Design (MS SQL), Troubleshooting, Version Control, Technical Documentation.