Semantic Data Modeler

About MIGx

MIGx is a global consulting company with an exclusive focus on the healthcare and life science industries, with their particularly demanding requirements on quality and regulatory aspects. We have been managing challenges and solving problems for our clients in the areas of compliance, business processes and many others.

MIGx interdisciplinary teams from Switzerland, Spain and Georgia have been taking care of projects in the fields of M&A, Integration, Application, Data Platforms, Processes, IT management, Digital transformation, Managed services and compliance.

Project Description

We are seeking a highly motivated and detail-oriented Semantic Data Modeler to join our innovative team. In this role, you will design, develop, and maintain semantic data models that form the backbone of intelligent data integration, knowledge discovery, and reasoning in complex domains such as life sciences. This position sits at the crossroads of data modeling, semantic standards, graph technologies, and AI-driven workflows, enabling advanced knowledge representation and data interoperability.

If you are passionate about connecting the dots across complex data ecosystems, thrive on precision and structure, and have a natural ability to think in terms of graphs, hierarchies, and relationships, this role is for you.

Responsabilities

1. Semantic Data Modeling

Design and maintain ontologies and vocabularies using RDF, RDFS, OWL, SKOS / SKOS-XL, DCT, DCAT, and many other standard ontologies

In collaboration with Business Analysists, translate business concepts into semantic models that support interoperability and reasoning

Ensure semantic models align with web standards (W3C, FAIR) and industry standards (CDISC, SNOMED CT, etc)

Apply validation logic and language (SHACL or ShEx) to ensure model and data quality

2. Graph Data Management

Model, store, and query data in graph databases (triple stores and property graph systems)

Use SPARQL and other graph query languages (e.g., GraphQL, Cypher, Gremlin) to retrieve and manage knowledge graphs

Optimize graph data pipelines for scalability, performance, and accuracy

3. Data Transformation & Integration

Design models as integrative parts of implement ETL / ELT pipelines to automatize knowledge extraction from structured and unstructured data into semantic / graph-based systems

Integrate semantic models to NLP techniques for semantic enrichment / annotation of text-derived knowledge

Collaborate with data engineers and scientists to ensure smooth ingestion and alignment of heterogeneous datasets

4. Quality & Governance

Define semantic data governance practices ensuring consistency, traceability, and reusability

Document modeling choices, schema evolution, and semantic mappings thoroughly

Contribute to metadata standards and data stewardship practices

5. Collaboration & Continuous Improvement

Work in an Agile / Scrum environment, delivering iterative improvements

Collaborate closely with cross-functional teams (data engineers, scientists, domain experts, AI specialists)

Contribute to DevOps and MLOps practices in semantic pipelines

6. Business Acumen :

Bring a as much understanding of the life sciences as possible, particularly in the context of biotech, and pharma sectors, to tailor solutions to industry-specific needs

Requirements - Must Have

Hard skills :

Proven extensive expertise in semantic standards : RDF, RDFS, OWL, SKOS / SKOS-XL, DCT, DCAT…

Hands-on experience with graph databases (e.g., GraphDB, Stardog, Neo4j, Amazon Neptune)

Strong proficiency in SPARQL; working knowledge of GraphQL, Cypher, or Gremlin

Familiarity with validation languages : SHACL is a must have

Solid understanding of data modeling principles and relational / NoSQL systems

Experience in ETL / ELT pipelines, NLP-based data integration, and data quality management

At ease with AI / ML workflows and the use of LLMs for semantic work

Soft skills :

Attention to detail and commitment to high-quality deliverables

Natural ability to connect the dots across abstract and concrete concepts

Strong working / semantic memory and ability to juggle complex model dependencies

A visual / graphical / 3D thinking brain : comfortable conceptualizing networks, hierarchies, and relationships

Excellent documentation and communication skills : able to explain semantic concepts clearly to senior managemen

Proactive, curious, and eager to explore and adopt emerging semantic technologies

Inventive : propose innovative approaches to model and manage data using graphical approaches

Requirements - Nice to have

Highly organized with strong personal knowledge management practices

Collaborative team player with the ability to influence and support other

A problem-solver who thrives in complex, multidisciplinary environments

Enthusiastic about life sciences, biotech, or pharma, with a desire to support research and innovation

What we offer

Hybrid work model and flexible working schedule that would suit night owls and early birds

25 holiday days per year

Possibilities of career development and the opportunity to shape the company future

An employee-centric culture directly inspired by employee feedback - your voice is heard, and your perspective encouraged

Different training programs to support your personal and professional development

Work in a fast growing, international company

Friendly atmosphere and supportive Management team.