Job Description & How to Apply Below
IFOM continuous success is ensured by the recruitment of highly selected undergraduate, graduate and post-graduate researchers from over 24 countries worldwide.
IFOM is hosted within a research campus shared with the European Institute of Oncology and the Italian Institute of Technology.
IFOM is committed to creating a safe and inclusive environment, based on mutual respect and the enhancement of diversity, offering equal job opportunities to all qualified candidates.
We seek for our Institute: Data Platform Developer
About the position
Candidate will report directly to the Head of Research Computing & Data Science and will be responsible for contributing to the development and day-to-day operation of IFOM’s research Data Platform – a governed, metadata-centric environment that manages research data across its entire lifecycle (acquisition, curation, movement, and publication) on a hybrid infrastructure. The role is primarily development-focused: building and extending the platform’s services and integrations, with the awareness needed to operate and troubleshoot the underlying infrastructure.
Working alongside the Research Computing & Data Science team and the platform’s implementation partner, the candidate will grow into progressive autonomy on the platform.
We are looking for a resource at the beginning of their career, with up to 2 years of experience; recent graduates with relevant project work are welcome to apply.
Candidate will be responsible for:
Developing and extending the platform’s services, data pipelines, and integrations, writing clean, maintainable, version-controlled code.
Building and maintaining data-ingestion and workflow-orchestration pipelines to acquire, validate, tier, and publish research data between storage systems and external repositories.
Implementing and maintaining data- and metadata-governance policies (validation, lifecycle, and tiering rules) and supporting the platform’s data catalog.
Operating and monitoring platform components running on containerized infrastructure, with enough awareness to inspect and troubleshoot the underlying infrastructure when needed.
Contributing to the platform’s security and compliance posture – access controls, auditing, and safe handling of sensitive research data – in line with GDPR and institutional policies.
Working with scientific facilities and research groups to translate their data workflows into platform integrations, treating the platform as a product researchers can rely on.
Applying sound engineering practice to all work: version control, automated testing and deployment, reproducible environments, and repeatable procedures rather than manual one-off steps.
Contributing to documentation, onboarding of research groups, and knowledge sharing within the team.
Qualification
This is a development-focused role designed for growth. The essential foundation is solid coding ability and, above all, a strong willingness to learn across data and platform engineering. The remaining skills will be developed on the job.
Programming in Python for scripting, automation, and data pipelines, with a focus on clean, maintainable code.
Solid command of Linux and the command line.
SQL and relational databases (e.g. PostgreSQL).
Fundamentals of containerization (Docker; Kubernetes is a strong plus).
Version control with Git.
Appreciated (and further developed on the job)
Data orchestration / integration tools (Apache Airflow, Apache NiFi, or equivalents).
Infrastructure automation and configuration management (Ansible; Helm, Terraform, or equivalents are a plus).
CI/CD pipelines and automated testing (e.g. Git Lab CI, Git Hub Actions).
Familiarity with microservices architectures and REST APIs.
Monitoring and observability tools (e.g. Prometheus, Grafana).
Awareness of data security and privacy practices (access control, auditing) and of GDPR obligations for sensitive data.
Exposure to HPC or bioinformatics environments.
Understanding FAIR data principles and data-catalog…
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