Remote Sensing Data Engineer
Organizational Context
The United Nations Environment Programme (UNEP) leads the global environmental agenda and advocates for action across the UN system. Its International Methane Emissions Observatory (IMEO) is a data-driven initiative focused on reducing methane emissions, a key contributor to climate change, aligning with the Paris Agreement. This role supports IMEO's mission by enhancing its data processing and analysis capabilities.
Job Purpose
This consultancy aims to ensure a reliable flow of satellite-detected methane emissions data into the Methane Alert and Response System (MARS). The role involves maintaining and improving the data ingestion pipeline, enhancing the estimation of source persistency and total annual emissions for methane point sources, and automating the publication of public data products on IMEO's Data Platform. The objective is to support accelerated methane emissions reductions through reliable, actionable data, contributing to global climate action and the Global Methane Pledge.
Responsibilities
Integrate new satellite data sources, including high-temporal-frequency geostationary sensors, into the MARS system, adjusting the PostgreSQL database schema as needed for smooth ingestion, processing, and storage. Share responsibility for the day-to-day monitoring and maintenance of the MARS data ingestion pipeline on Azure, triaging and resolving ingestion issues in Jira and production. Extend MARS data quality monitoring checks to cover new data sources and processing steps. Own and improve the MARS source persistency pipeline for estimating source persistency and total annual emissions for methane point sources. Maintain and automate public data pipelines, including plume and source exports and the top 50 emitters list.
Work Experience
Experience in building or maintaining operational data pipelines and data quality monitoring systems, including issue tracking with tools like Jira. Demonstrated scientific expertise in remote sensing, particularly in retrieving and interpreting atmospheric trace gases from satellite imagery. Experience with software engineering best practices such as version control (Git), containerization (Docker), and CI/CD.
Skills
Proficiency in Python and its scientific/geospatial stack for data processing. Experience with PostgreSQL, cloud platforms (preferably Azure), and software engineering best practices. Expertise in remote sensing data analysis. Experience with data pipelines and monitoring systems. Familiarity with issue tracking tools (Jira).