Overview
The Data Engineer will design, build, and maintain data pipelines and ETL/ELT processes to ingest, clean, transform, and deliver environmental, administrative, and partner data into UNEP's corporate data platforms. The role also involves supporting the operation of data platforms, ensuring data quality, and collaborating with various teams.
Key Responsibilities
- Design, build and maintain secure, performant and reusable data pipelines and ETL/ELT processes.
- Implement internal process improvements to automate manual ingestion and optimize data delivery.
- Develop and maintain data catalogues, metadata and lineage.
- Apply infrastructure-as-code and CI/CD practices in the deployment of data pipelines.
- Support the operation of UNEP's enterprise data lakes, data warehouses and analytics platforms.
- Implement and monitor data quality controls.
- Contribute to the configuration and optimization of cloud and hybrid data infrastructure.
- Produce and maintain technical documentation, runbooks and standard operating procedures.
- Ensure data ingestion, storage and delivery comply with UN and UNEP policies on information security, privacy, protection of personal data and classification.
- Implement role-based access control, encryption, secrets management and secure API integrations.
- Support the application of UNEP's digital and data standards, common taxonomies and interoperability frameworks.
- Work closely with data analysts, data scientists, GIS specialists and application developers.
- Provide technical support to programme units.
- Participate in agile ceremonies, technical reviews and UNEP-wide digital communities of practice.
Required Experience
- A minimum of five (5) years of progressively responsible experience in data engineering, data integration, data management or related area is required.
- Experience building and operating data pipelines from multiple sources, using ETL/ELT tools, is required.
- Experience with database programming languages (SQL) and at least one high-level programming language used in data engineering (such as Python) is required.
- Experience with version control and CI/CD toolchains (e.g. Git, GitLab/GitHub, Jenkins, Azure DevOps) for deploying data workflows is required.
- Experience with cloud or hybrid data infrastructure and with the deployment of data solutions in containerized environments is desirable.
- Experience working in or with UN entities, international organizations or other large, distributed organizations is desirable.
Qualifications
- Advanced university degree (Master's degree or equivalent) in computer science, information systems, data management, engineering or a related field is required.
- A first-level university degree in combination with two additional years of qualifying experience may be accepted in lieu of the advanced university degree.
