Data&Knowledge platform Engineer

SICPA HOLDING SA
Madrid, Spain
5 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience required
5 years minimum
Working hours
Regular working hours
Job source

Tech stack

Geographic Information Systems Application Programming Interfaces (APIs) Artificial Intelligence Amazon Web Services Automation of Tests Microsoft Azure Databases Continuous Integration Information Engineering Relational Databases Graph Database Monitoring of Systems
+21 more
Python (Programming Language) Machine Learning Enterprise Messaging Systems Neo4j Open Source Intelligence Operational Databases PostGIS Resource Description Framework (RDF) Software Engineering SPARQL SQL Databases Technical Data Management Systems Workflow Management Systems Retrieval-Augmented Generation Large Language Models Agentic-AI Information Technology Data Management Entity Resolution Data Pipelines Docker

Job description

  • Design and implement scalable pipelines for structured, unstructured, geospatial, OSINT ( Open source intelligence) and SICPA data.
  • Define reusable data models supporting relational, graph, geospatial and AI workloads.
  • Build capabilities for data quality, enrichment, entity resolution, provenance and lineage.
  • Develop and operate data platforms, repositories and APIs for applications such as SICPA Pulse.
  • Operationalise taxonomies, ontologies and knowledge graphs.
  • Prepare reliable data pipelines for RAG systems and AI agents.
  • Implement testing, CI/CD, monitoring and observability for data products.
  • Collaborate with data scientists, software engineers, domain experts and academic partners to productionise analytical and graph-based solutions.

Requirements

  • Master’s degree in Computer Science, Data Engineering, Software Engineering or a related field, with 5+ years of experience building production data platforms.
  • Strong proficiency in Python and SQL.
  • Experience integrating heterogeneous data from APIs, databases, files or messaging systems.
  • Solid knowledge of data modelling, schema evolution, data quality, lineage and provenance.
  • Experience with workflow orchestration, automated testing, Docker and CI/CD.
  • Experience with relational databases and at least one additional data technology such as graph, document, vector, search or geospatial databases.
  • Strong software-engineering and problem-solving skills.
  • Excellent communication skills with technical and non-technical stakeholders

Preferred qualifications

  • Knowledge graphs and technologies such as Neo4j, Cypher, RDF or SPARQL.
  • Ontology, taxonomy or semantic-data modelling.
  • Entity resolution, record linkage and temporal data modelling.
  • Geospatial data engineering, including PostGIS or GeoJSON.
  • Data pipelines for RAG, LLM and agentic systems.
  • Experience with OSINT, multilingual, government, financial or fraud-related data.
  • Familiarity with graph analytics or graph machine learning.
  • Experience with Azure, AWS, hybrid or on-premise deployments.

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