
Job ID: SSCItaly-Copernicus Data Quality
Deadline: 20 August 2025
On behalf of the Italian subsidiary of the group – SSC Italy – we are helping to strengthen the Service Team supporting the Copernicus Data Quality and the Copernicus Contributing Mission Activity, at ESA/ESRIN in Frascati (RM), Italy.
We are always seeking passionate individuals with a strong background in space engineering. If you are driven, ambitious, and eager to make a significant impact in the space industry, apply now and embark on an extraordinary space journey with us.
Specific Tasks
The activities consist of 2 Service Packages, and the scope of the work include the following tasks and responsibilities:
Service Package 1 – Copernicus Data Quality Activities
- Perform independent assessment of Mission Performance Cluster (MPC) outputs for all Sentinel missions (S-1, S-2, S-3, S-5P).
- Coordinate and review the Fiducial Reference Measurements (FRM) activities across mission domains, providing feedback on methodology, quality, and relevance.
- Support ESA in monitoring geophysical product performance and trends across the Copernicus Sentinel missions.
- Provide technical input to ESA on calibration and validation (Cal/Val) planning and execution.
- Contribute to the development and maintenance of data quality dashboards, anomaly reports, and traceability documentation.
- Liaise with Copernicus Services and Cal/Val stakeholders to consolidate requirements and ensure cross-service coherence.
Service Package 2 – Sentinel-1, Sentinel-2 and Copernicus DEM
- Support the Sentinel-1 and Sentinel-2 Mission Management teams with expert technical advice on acquisition planning, data quality, and anomaly handling.
- Coordinate the validation and evolution of the Copernicus Digital Elevation Model (DEM), supporting performance analysis and interface with the contractor.
- Review and validate Level-1 and Level-2 data quality metrics, tools, and processing chains related to Sentinel missions.
- Assist in technical documentation, reviews, and reporting for data quality anomalies, updates, and reprocessing campaigns.
- Interface with ESA engineers, MPCs, and external contractors to ensure timely and accurate feedback loops.
Specific Requirements
- Educational background in Remote Sensing, Earth Observation, Geoinformatics, Physics, Engineering, or a related scientific field (MSc or higher).
- Minimum 3 years of professional experience in EO mission performance, data quality analysis, or calibration/validation activities.
- Proven knowledge of Sentinel missions (especially S-1 and S-2) and familiarity with Copernicus data products and ground segment operations.
- Experience in EO data analysis, including tool development (e.g. Python, MATLAB, IDL) and quality reporting.
- Understanding of geophysical validation methods, Cal/Val protocols, and the role of FRM.
- Familiarity with Copernicus DEM validation and usage in EO applications is a strong asset.
- Excellent analytical and reporting skills, attention to detail, and ability to work in an international team.
- Strong written and spoken English is mandatory; knowledge of another ESA Member State language is an asset.
Legal and Security Requirements
- Applicants must be legally allowed to work in the EU and hold a European citizenship. Evidence of eligibility will be required from candidates as part of the recruitment process.
- Copy of passport and degree(s) certificate.
- Good conduct certificate from the country where currently resident.
- Furthermore, in view of the nature of the work, all potential employees will undergo stringent reference checks.
Location
The work will be performed on-site/near-site at ESRIN, in Frascati (RM), Italy.
Contract
- Competitive remuneration package, recognizing the value of your skills and expertise.
- Unique career opportunities, including the possibility of working in other countries with our SSC Group.
- Personalized training and development programmes.
To be considered for this Position
Prior to 20 August 2025, please apply via our Job Application form quoting SSCItaly-Copernicus Data Quality as reference.
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