Data and Knowledge Graph Engineer

Data and Knowledge Graph Engineer 

About Reply:

Reply specialises in designing and implementing solutions based on new communication channels and digital media. Structured as a network of highly specialised companies, Reply supports leading European industrial groups in sectors such as Telco & Media, Industry and Services, Banking and Insurance, and Public Administration, helping define and develop business models enabled by new paradigms such as AI, Cloud Computing, Digital Media, and the Internet of Things. Reply’s services include Consulting, System Integration, and Digital Services.   

Role Overview:

This role focuses on designing and building semantic layers that give organisations a single, shared and machine-readable understanding of their business. You will work across diverse industries, translating complex domains into ontologies and knowledge graphs that connect data, systems, applications and AI solutions. From discovery and modelling through to production, you will own the end-to-end technical design, creating robust foundations for integration, governance, analytics and generative AI.

Responsibilities:

• Facilitate discovery workshops with business and technical stakeholders to understand and model key domains. 


• Design, build, and maintain scalable ontologies, taxonomies, and semantic models that reflect complex business concepts.  


• Develop and operate knowledge graphs end-to-end, including data ingestion, mapping, and entity resolution pipelines.  


• Connect and standardise data across disparate systems using semantic technologies to improve integration and data consistency.  


• Create, optimise, and maintain graph queries, exposing graph data via APIs and services for downstream consumers. 


• Integrate knowledge graphs with AI solutions to deliver grounded, trustworthy insights for analytics and generative AI use cases.  


• Prototype and productionise AI-powered features, including prompt engineering, evaluation, and continuous improvement.  


• Advise customers on semantic architecture, governance, and best practices, contributing reusable standards and frameworks.

About the Candidate:

• Degree in Computer Science, Computational Linguistics, Information Science, or a related field, or equivalent hands-on experience.  


• Proven track record delivering semantic layers, ontologies, and knowledge graphs into production environments.  


• Strong understanding of semantic web technologies and knowledge representation (e.g. RDF, OWL, SPARQL, Cypher) and experience with graph databases such as Neo4j or GraphDB.  


• Solid programming skills in Python (or similar) for data integration, pipeline development, and automation. 


• Experience with modern data architectures, including data lakes/warehouses, governance frameworks, and master/metadata management.  


• Hands-on experience with Generative AI and LLMs, including RAG, embeddings, vector search, GraphRAG, prompt engineering, and agent frameworks (e.g. LangChain, LlamaIndex). 


• Strong stakeholder skills, able to quickly understand complex business domains and communicate technical concepts to non-technical audiences. 


• Experience working in cloud environments (preferably Azure) with good knowledge of Git, CI/CD, containers, and client-facing delivery practices.