PFor our client, international consulting company expert in SAAS platforms building, we are looking for a: /p p bKnowledge Graph Data Infrastructure Engineer /b /pbr/br/pbResponsabilità /b /pp bKey Responsibilities /b /p ulliDesign and implement the Strategy Knowledge Graph and its underlying schema. /liliBuild mechanisms to track how entities and relationships change over time. /liliSet up a federated graph architecture that separates public knowledge from private client data. /liliDefine node and edge structures with essential metadata and provenance. /liliOptimize graph queries and retrieval patterns for complex reasoning tasks. /liliManage and integrate multiple storage systems (graph, vector, metadata, documents, blobs). /liliMaintain consistency across storage layers through event-driven synchronization. /liliBuild the hybrid retrieval API that unifies graph and vector results for the reasoning agents. /liliImplement caching and partitioning strategies to ensure performance and multi-tenant scalability. /liliBuild ETL pipelines to ingest processed documents and transform them into graph entities and relationships. /li /ul p· Implement data normalization, entity resolution, and incremental updates to keep the graph clean and scalable. /p p· Ensure data quality and temporal consistency across the knowledge base. /p p· Maintain full provenance so every fact is traceable to its source. /p p· Develop APIs (REST/GraphQL) for querying, updating, and interacting with the Knowledge Graph. /p p· Optimize database performance through indexing, caching, and query tuning. /p p· Implement access control, encryption, audit logging, and compliance mechanisms across the data layer. /pbr/br/pbProfilo /b /pp bExperience Background /b /p ulli3–6+ years of professional experience as a Data Engineer, Backend Engineer, or Knowledge Graph Engineer, working on production-grade data systems. /liliStrong hands-on experience with graph databases (e.g. Neo4j, TigerGraph, Amazon Neptune, or equivalent) including schema design, query optimization, and performance tuning. /liliSolid experience designing and operating distributed data infrastructure in cloud environments (AWS, GCP, or Azure). /liliProven ability to design data models and schemas for complex domains, including entities, relationships, and metadata. /liliExperience implementing ETL / ELT pipelines for structured and unstructured data, including incremental updates and backfills. /liliStrong understanding of data consistency, versioning, and provenance in large-scale data systems. /liliExperience integrating multiple storage systems (e.g., graph DB + relational DB + document store + object storage) into a coherent data platform. /liliPractical experience building APIs for data access (REST and/or GraphQL) and integrating them into backend services. /liliFamiliarity with event-driven architectures (e.g., message queues, streaming, async pipelines) for synchronizing distributed systems. /liliStrong skills in Python, Java, or Scala for backend and data engineering workloads. /liliExperience with query optimization, indexing strategies, caching, and partitioning for high-performance data access. /liliUnderstanding of security, access control, and data isolation in multi-tenant SaaS platforms. /liliStrong grasp of software engineering best practices: version control, testing, CI/CD, monitoring, and documentation. /li /ulbr/br/p«I candidati, nel rispetto del D.lgs. 198/2006, D.lgs. 215/2003 e D.lgs. 216/2003, sono invitati a leggere l’informativa sulla privacy consultabile sotto il form di richiesta dati della pagina di candidatura (Regolamento UE n. 2016/679).br L’offerta è rivolta a candidati di entrambi i sessi, nel rispetto del D.lgs. 198/2006 e della normativa vigente in materia di pari opportunità. L’azienda promuove un ambiente di lavoro inclusivo e garantisce pari opportunità a tutte le persone, indipendentemente da genere, età, origine, orientamento sessuale o disabilità.» /pbr/br/