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# Data Engineer For Ai Systems

- **Company:** Enfint
- **Location:** Madrid, Spain (Remote available)
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Amazon S3, Continuous Integration, Information Engineering, Data Governance, Data Infrastructure, Extract Transform Load (ETL), Database Queries, IBM Software, Python (Programming Language), PostgreSQL, Meta-Data Management, Microsoft Office, Pattern Recognition, Search Technologies, Microsoft SharePoint, Software Engineering, SPARQL, SQL Databases, Unstructured Data, Git, Data Layers, Information Technology, Data Lineage, Full-text Search, Data Pipelines, Docker
- **Published:** September 16, 2026
- **Apply:** https://www.buscojobs.com.es/data-engineer-for-ai-systems-en-madrid-ID-370523974

## About the Role

4-5 Years of experience in Data Engineering, Software Engineering, or AI Engineering with solutions deployed in production Advanced Python (P3 - Advanced) and SQL proficiency Practical experience modeling and developing queries with Gremlin, SPARQL, and/or Cypher Solid AWS experience with S3, Glue, and Aurora PostgreSQL Experience designing batch and incremental ETL/ELT pipelines Experience with Docker, CI/CD, and Git Experience with hybrid retrieval architectures combining SQL, graph, and vector search Knowledge of data lineage, cataloging, metadata management, and data quality frameworks Degree or Master's in Computer Science, Mathematics, Physics, Engineering, or a related field Spanish at C1 (Expert) level English at B2 (Advanced) level Nice to have: Neptune and AWS Bedrock ???????
Hybrid schedule with 40% telework / remote work; Office schedule.

## Description

act digital designs semantic data layers and knowledge base solutions that power enterprise-scale artificial intelligence systems.??????Design graph schemas, entity resolution strategies, ontological structures, and semantic indexing systems to support agentic AI Ingest and transform structured and unstructured data from S3, SharePoint, FileNet, and other sources while ensuring semantic consistency Create taxonomies and ontologies using RDF, OWL, and SKOS standards Operate and orchestrate AWS services including S3, Glue, Aurora PostgreSQL, Neptune, and AWS Bedrock Build RAG pipelines, semantic search, metadata enrichment, and Text-to-SQL interfaces Design graph retrieval strategies combining pattern matching, vector search, full-text search, and relational traversals Ensure quality control, monitoring, and production readiness of AI data infrastructure ??????????4-5 Years of experience in Data Engineering, Software Engineering, or AI Engineering with solutions deployed in production Advanced Python (P3 - Advanced) and SQL proficiency Practical experience modeling and developing queries with Gremlin, SPARQL, and/or Cypher Solid AWS experience with S3, Glue, and Aurora PostgreSQL Experience designing batch and incremental ETL/ELT pipelines Experience with Docker, CI/CD, and Git Experience with hybrid retrieval architectures combining SQL, graph, and vector search Knowledge of data lineage, cataloging, metadata management, and data quality frameworks Degree or Master's in Computer Science, Mathematics, Physics, Engineering, or a related field Spanish at C1 (Expert) level English at B2 (Advanced) level Nice to have: Neptune and AWS Bedrock ???????Hybrid schedule with 40% telework / remote work; Office schedule.#J-*****-Ljbffr


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