Semantic Data Modeler

MIGx AG; Barcelona; Hybrid; EUR 60,000 - 90,000; Full time

Benefits offered by this job

Hybrid work model

25 holiday days per year

Career development

Employee-centric culture

Training programs

International company

Friendly atmosphere

Job summary

MIGx is a global consulting firm focused on healthcare and life sciences, seeking a Semantic Data Modeler to design and maintain semantic data models enabling data integration, knowledge discovery, and reasoning across complex domains.

You will work at the intersection of data modeling, semantic standards, graph technologies, and AI-driven workflows, collaborating with cross-functional teams to deliver scalable solutions in life sciences.

Qualifications

• 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
• Attention to detail and commitment to high-quality deliverables
• Natural ability to connect the dots across abstract and concrete concepts
• 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 management
• Proactive, curious, and eager to explore and adopt emerging semantic technologies
• Inventive: propose innovative approaches to model and manage data using graphical approaches

Responsibilities

• Semantic Data Modeling: design ontologies and vocabularies using RDF, RDFS, OWL, SKOS/SKOS-XL, DCT, DCAT.
• Translate business concepts into semantic models to support interoperability and reasoning.
• Ensure models align with web standards (W3C, FAIR) and industry standards (CDISC, SNOMED CT).
• Apply validation logic and SHACL or ShEx to ensure data quality.
• Graph Data Management: model, store, and query data in graph databases; use SPARQL and GraphQL/Cypher/Gremlin.
• Optimize graph data pipelines for scalability, performance, and accuracy.
• Data Transformation & Integration: design models for ETL/ELT pipelines to extract from structured and unstructured data into semantic/graph systems.
• Integrate semantic models with NLP techniques for semantic enrichment of text-derived knowledge.
• Collaborate with data engineers and scientists to ensure smooth ingestion and alignment of heterogeneous datasets.
• Quality & Governance: define semantic data governance, document mappings, and contribute to metadata standards.
• Work in an Agile/Scrum environment, delivering iterative improvements and collaborating with cross-functional teams.
• Contribute to DevOps and MLOps practices in semantic pipelines.
• Business Acumen: leverage life sciences knowledge to tailor solutions for biotech and pharma needs.

Skills

Semantic standards

Graph databases

SPARQL

Validation languages

Data modeling

ETL/ELT pipelines

NLP integration

AI/ML workflows

Documentation

Tools

GraphDB

Stardog

Neo4j

Amazon Neptune

SPARQL engines

Job description

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
• 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

• 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
• 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.