Threat Information Data Engineer (Normalisation, Quality andProvenance) for NATO with security

Every threat feed is a different shape. Somebody has to make them one thing, and make it trustworthy. You would engineer the data side of a defence alliance's threat-intelligence sharing platform in Mons, Belgium — the pipelines feeding it, the schema underneath it, and the quality rules that decide what is worth keeping. What you would be doing Designing, building and maintaining the pipelines that ingest threat information from a wide range of sources Developing and maintaining Python scripts that automate the platform and integrate it with the systems around it, including security monitoring and detection Defining, documenting and implementing the rules by which information is disseminated Supporting the work around threat-information process management Normalising heterogeneous feed structures into one consistent schema Enforcing data quality — deduplication, confidence scoring, indicator lifecycle, provenance, and tracking and filtering the low-quality sources Contributing to and integrating existing cyber threat information standards Creating and maintaining the documentation on the taxonomies and galaxies people actually use Writing and keeping current the best-practice guidance for data entry Being the expert the internal communities come to on curation and dissemination options — what each one buys them and what it costs Supporting the user community — regular feedback normally, daily feedback during exercises Leading a team of platform operators during exercises, covering information flow, quality control and user management Planning, preparing and delivering online training, and helping build the individual training packages that prove the objectives were met What you would bring At least ten years of practical experience across the areas below Designing, building and managing data pipelines — transformation, data models, schemas, metadata and workload management Supporting, leading or managing data-focused operations and projects, using data engineering tooling behind data science, analytics and visualisation Python scripting A good grasp of security principles, practice, concepts and technology The ability to work alone and in a team Excellent organisation, communication and writing Professional English A bachelor's degree in a related discipline with three years of related experience — or, exceptionally, ten years of progressive expertise in this kind of work Nice to have The platform's own core format, and STIX Work as a cyber threat intelligence analyst, or as an incident responder Splunk Handling cyber threat information at scale Work with open-source communities, and multinational cyber exercises Administering a threat-sharing platform, or writing code for one in Python or PHP Why this one is worth a look Data engineering where the data is adversarial and the quality rules genuinely matter — not another warehouse.