Remote Sensing Data Engineer

The Remote Sensing Data Engineer consultant will provide a reliable flow of satellite detections into MARS from both existing and newly integrated data sources; maintain and improve the ingestion pipeline and source persistency estimation; and automate public data products on IMEO’s Data Platform. The role involves integrating new satellite data sources, monitoring data pipelines, and enhancing methane emissions estimation aligned with climate action goals.

Responsibilities

• Integrate new satellite data sources into the MARS system, including high-temporal-frequency geostationary sensors and adjust the PostgreSQL database schema accordingly
• Monitor and maintain the MARS data ingestion pipeline running on Azure, triage ingestion issues in Jira and resolve them in production
• Extend MARS data quality monitoring checks to cover new data sources and processing steps
• Own and improve the MARS source persistency pipeline estimating source persistency and total annual emissions for methane point sources
• Maintain and automate public data pipelines for plume and source exports, top 50 emitters list, and detection/non-detection time series

Requirements

• First-level Degree (e.g. Bachelors) in Remote Sensing, Computer Science, Data Science, Physics or a related field (optional)
• High proficiency in Python and its scientific and geospatial stack, applied to data processing and analysis tools, for satellite remote sensing data
• Experience with PostgreSQL, cloud platforms – preferably Azure, and ideally its ML and web app services – and software engineering best practices: version control (Git), maintainable and tested code, containerization (Docker), and CI/CD (Jenkins or similar)
• Scientific expertise in remote sensing, demonstrated through open-source projects or scientific publications, with particular interest in the retrieval and interpretation of atmospheric trace gases from satellite imagery
• Experience building or maintaining operational data pipelines and data quality monitoring systems, including issue tracking with tools such as Jira
• A genuine interest in environmental and climate-related challenges, demonstrated through academic projects, personal research, open-source contributions or independent learning

Skills

• Python Programming
• Geospatial Data Processing
• High-resolution Satellite Remote Sensing
• PostgreSQL
• Azure Cloud Infrastructure
• Machine learning services
• Web app services
• Software Engineering Practices
• Version Control with Git
• Containerization with Docker
• Continuous Integration
• Jenkins
• Remote Sensing Data Processing
• Atmospheric trace gas retrieval
• Data Pipeline Development
• Data Quality Monitoring
• Issue tracking with Jira
• Scientific Research
• Environmental Data Interpretation
• Climate Data Interpretation

Languages

English