Senior Engineer - Engineering Services

Planet Pharma; Madrid; Presencial; EUR 60.000 - 85.000; Jornada completa

Descripción de la vacante

A leading data solutions company based in Madrid is seeking a skilled knowledge graph developer to design and maintain formal ontologies and create high-performance graph queries. The ideal candidate will have over 5 years of experience in large-scale knowledge graph design and strong expertise in ontology and semantic modeling. This role entails working collaboratively with cross-functional teams to implement solutions for AI and machine learning applications. This position offers a dynamic environment with opportunities for innovation.

Formación

• 5+ years of experience designing and implementing large-scale knowledge graphs.
• Strong expertise in ontology engineering and semantic modeling.
• Proficiency with at least one major graph database.

Responsabilidades

• Design and maintain formal ontologies and semantic models.
• Build and optimize knowledge graph architectures.
• Develop scalable data pipelines and ETL processes.
• Create advanced graph queries and implement algorithms.
• Collaborate with cross-functional teams to translate business needs.

Conocimientos

Ontology engineering

Semantic modeling

Graph database proficiency

Programming in Python

NLP techniques

Problem-solving abilities

Collaboration in agile environments

Graph algorithms

Educación

Master's or Ph.D. in Computer Science, AI, or related field

Herramientas

Neo4j

AWS Neptune

Google Cloud Platform

Descripción del empleo

Key Responsibilities

Ontology & Semantic Modeling :

Design and maintain formal ontologies and semantic models (e.g., RDF, OWL) to accurately represent complex domain knowledge and relationships within a knowledge graph.

Graph Architecture & Development :

Build and optimize knowledge graph architectures using leading graph database technologies (e.g., Neo4j, JanusGraph, Amazon Neptune).

Data Integration & ETL :

Develop scalable data pipelines and ETL processes to ingest, transform, and map diverse data sources into graph structures while ensuring data quality and consistency.

Querying & Analytics :

Create advanced, high-performance graph queries (e.g., Cypher, SPARQL) and implement graph algorithms (e.g., shortest path, community detection) to deliver actionable insights.

Cross-Functional Collaboration :

Partner with Data Scientists, ML Engineers, Product Managers, and domain experts to translate business needs into technical solutions that power search, recommendations, and AI / ML applications.

Performance Optimization :

Monitor and tune graph database performance and associated pipelines for scalability and real-time query efficiency.

Essential Requirements

• ~5+ years of experience designing and implementing large-scale knowledge graphs in production environments.
• ~ Strong expertise in ontology engineering, semantic modeling, and familiarity with standards such as RDF, RDFS, OWL, and SPARQL.
• ~ Proficiency with at least one major graph database (e.g., Neo4j, TigerGraph, AWS Neptune).
• ~ Hands‑on experience integrating LLMs with knowledge graphs (e.g., RAG, KG‑powered AI agents).
• ~ Solid programming skills, primarily in Python.
• ~ Experience applying NLP techniques for text processing and structuring (e.g., NER, relation extraction).
• ~ Strong problem‑solving abilities and collaborative mindset in fast‑paced, agile environments.
• ~ Familiarity with graph algorithms and libraries (e.g., Neo4j GDS, NetworkX).
• ~ Excellent communication skills to explain complex AI concepts to technical and non‑technical audiences.

Desired Skills (Nice to Have)

• Advanced degree (Master’s or Ph.D.) in Computer Science, AI, or related technical field.
• Contributions to research or open‑source projects.
• Experience with Google Cloud Platform and Vertex AI.
• Knowledge of NLP techniques for entity and information extraction to populate knowledge graphs.
• Familiarity with Graph Machine Learning (e.g., Graph Neural Networks).