Senior Data Engineer (Ispra, on-site) – European Commission

TheWhiteam; Ispra; In loco; EUR 58.000 - 62.000; Tempo pieno

Descrizione del lavoro

TheWhiteam in Ispra, Italy, seeks a Senior Data Engineer to support the FASST tool within the JRC.C5 framework. The role covers data management, model validation, and tooling development for air quality assessments under EU climate policies.

You will maintain data pipelines, integrate environmental datasets, apply AI techniques, and ensure data quality across model runs, with on-site collaboration for multi-stakeholder studies.

Competenze

• Master's or Bachelor's degree in a related field.
• At least 4 years of relevant professional experience.
• Experience authoring scientific documentation or reports.
• Knowledge of surrogate air quality and Integrated Assessment models is preferred.

Mansioni

• Maintain and test FASST tool across R updates.
• Develop and enhance FASST modules for new scientific developments.
• Operate FASST for specific study needs and policy support.
• Build and optimise data pipelines using R, Python and SQL.
• Validate inputs/outputs by comparing with observations and other models.

Conoscenze

R

Python

SQL

AI tools

Data engineering

Formazione

Bachelor's or Master's in CS/Engineering/IS

Strumenti

FASST tool

R scripting

Descrizione del lavoro

Role: Senior Data Engineer in support of FASST.

Place of performance: Ispra (Italy). European Union, represented by the European Commission, Joint Research Centre in Ispra, Clean Air and Climate Unit.

Modality: Onsite.

Duration: 36 months.

Rate/budget on offer: 315€-335€/day.

The Clean Air and Climate Unit (JRC.C5) supports the implementation of legislation on air quality and climate change, as well as international agreements, at European, international and global levels. JRC.C5 developed the Fast Assessing and Screening Tool (FASST) for integrated air quality assessment modelling, supporting the design of decarbonisation and energy-transition policies, with particular reference to air pollution, its impacts on health and ecosystems, and the co-benefits of air quality and climate policies.

The FASST tool is used in studies covering Member States, candidate and neighbourhood countries, as well as at the global level. JRC.C5 supports other Commission services (DG ENV, DG ENEST, DG MENA and DG RTD) in monitoring and implementing the EU acquis under Chapter 27 on Environment and Climate Change in accession and neighbourhood countries. It also contributes to the revision of the Gothenburg Protocol to the Air Convention (CLRTAP) and supports international and global studies in collaboration with international organisations such as WHO, UNEP, the World Bank and the OECD.

The scope of the contract is to provide scientific data management support to the SCENARIO project team for the development, maintenance, optimisation and operation of the FASST tool including retrieval of datasets with input variables for model execution and testing, model validation by comparison with measurements (ground-based and satellite) and results from other models (including chemical transport models, Gaussian models, Lagrangian models and statistical models) and data fusion.

Job Description

• Task 1. Maintenance of FASST tool. The objective of this task is to guarantee the functionality of the FASST tool by continuous testing of the model routines to address changes in the version of the R script language used to develop the tool, resolution of program bugs or manage inconsistencies in the results.
• Task 2. Development of FASST tool. The objective of this task is to contribute to the development of the FASST tool by supporting the improvement of the existing model modules and the creation of new ones addressing new scientific and technological developments and/or new policy areas requiring scientific support.
• Task 3. Operation of the FASST tool. The objective of this task is to support the setup and operation of the FASST tool according to the results needed for every specific study or policy support activity.

Main Responsibilities

• Develop, maintain and optimise data pipelines and workflows supporting the FASST tool, using R, Python and SQL.
• Retrieve, process, integrate and manage environmental and air-quality datasets required for FASST model execution, testing and analysis.
• Validate FASST inputs and outputs by comparing model results with ground-based and satellite observations and with results from other air-quality models.
• Implement data fusion and quality-control procedures to ensure the consistency, reliability and traceability of datasets used by the FASST modelling framework.
• Support the development and operation of FASST, including the implementation and testing of new functionalities, data sources and modelling workflows.
• Apply data engineering and AI/machine-learning techniques to improve the processing, analysis and use of environmental data and to support scientific assessments of air pollution and its impacts.

Specific Expertise, Knowledge And Skills

• Experience in data elaboration and/or engineering using R, Python and SQL for the integration, processing, validation and management of air quality and other environmental datasets.
• Experience with AI tools for quantitative environmental data management and analysis (machine learning, data engineering).
• Experience in the use of surrogate air quality and integrated assessment models (e.g. FASST tool) implemented in R script language.

Minimum requirements

• Master's or Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field.
• At least 4 years of relevant professional experience in similar positions.
• The ideal candidate should have contributed as an author or co-author to scientific documentation published by an independent authority, as well as to reports from official institutions or peer-reviewed publications, supporting or relating to the use of surrogate air quality and integrated assessment models (e.g. the FASST tool) implemented in R. Experience in this area is the main focus of this mission.

Desirable

• Relevant certifications in relevant data engineering areas.
• Knowledge of additional EU languages.
• Experience in international or European institutions or large-scale multi-vendor projects.