2 months ago
Barcelona, SpainSenior
Responsibilities
- Design, build, evolve, and deploy production knowledge graphs in Stardog.
- Model ontologies, taxonomies, and vocabularies using RDF, RDFS, OWL, SKOS, and SHACL.
- Write, optimize, and troubleshoot SPARQL queries, rules, and inference over large graphs.
- Integrate relational, API, file, and semi-structured sources through virtual graphs and mappings such as R2RML.
- Lead discovery sessions with subject matter experts and translate business questions into competency questions and semantic models.
- Align models with life science standards and public ontologies, including identifier mapping and entity resolution.
- Automate graph builds, tests, and deployments using Python and Git-based CI/CD workflows.
- Embed data quality, validation, reconciliation, governance, lineage, and reusable semantic assets into the graph lifecycle.
- Document models, enable colleagues, and contribute to agile team ceremonies and continuous improvement.
Requirements
- Hands-on experience delivering production knowledge graph solutions with Stardog; experience with GraphDB, Amazon Neptune, Virtuoso, or Anzo may transfer.
- Strong command of RDF, RDFS, OWL, SKOS, SHACL, and SPARQL.
- Practical experience with ontology and taxonomy modeling, stakeholder discovery, and production semantic models.
- Experience mapping and virtualizing relational and semi-structured sources into graphs.
- Solid Python and SQL skills for data preparation, transformation, automation, and troubleshooting.
- Familiarity with Git-based workflows and CI/CD, including GitHub Actions or Azure DevOps.
- Experience with life science or healthcare data and its quality and regulatory expectations.
- Ability to scope work independently, propose and defend approaches, and take ownership.
- Working knowledge of data quality, validation frameworks, and test-driven data development.
- Experience working in agile environments such as Scrum or Kanban.
- Professional working proficiency in English.
- Preferred: familiarity with SNOMED CT, MeSH, ChEBI, UMLS, LOINC, CDISC, SDTM, RIM, IDMP, GxP, FAIR data principles, GraphRAG, vector search, LLM-assisted ontology work, Neo4j, data lineage/catalog/governance tooling, Terraform, Bash, PowerShell, Docker, or Kubernetes.
- Local language skills such as Spanish, Catalan, or Georgian are a plus.
Benefits
- Hybrid work model with a flexible schedule.
- 25 holiday days per year.
- Free English classes.
- Career development opportunities and the opportunity to help shape the company’s future.
- Employee-centric culture informed by employee feedback.
- Training programs supporting personal and professional development.
- International company with a friendly atmosphere and supportive management team.
Categories
Data Engineering
About MIGx AG
MIGx AG is a Basel (BS)-headquartered, privately held IT services consultancy focused on life sciences. It builds and operates data platforms, cloud-native pipelines, and AI/advanced analytics for pharmaceutical, biotechnology, medical device, and diagnostics companies, with offerings spanning data strategy, governance, engineering, and compliant architectures. Revenue comes from consulting and end-to-end project delivery across regulated R&D, clinical, and commercial use cases.