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Publié il y a 18 jours

Context Engine - GCP Data and graph engineer

@ Querentia Inc.

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Toronto, Ontario

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Postuler
SIGNAUX

En bref

Querentia Inc. is hiring a Data & Graph Engineer on a contract-to-hire basis (possible 3-month CTH) in Toronto, Ontario, with a hybrid work mode. The role builds graph-driven data platforms, search infrastructure and event-based architectures, including knowledge graphs, Cypher/Neo4j queries and Elasticsearch/OpenSearch. Candidates need strong graph modeling and search datastore experience and a grasp of cache and index invalidation.

Responsabilités :

  • Model business domains as scalable graph structures
  • Write and tune Cypher and GraphQL queries
  • Build knowledge graphs and search with Elasticsearch/OpenSearch and vector databases
  • Build pipelines and event-driven invalidation to keep systems in sync

Résumé des exigences :

  • Strong graph data modeling and Cypher (Neo4j) expertise
  • Hands-on Elasticsearch or OpenSearch experience
  • Experience building and managing knowledge graphs
  • Understanding of cache and index invalidation
  • Experience with event-driven architectures and real-time sync

Outils et compétences

Neo4jElasticsearchOpenSearchGCPKubernetesTerraform
Source et dates

Type de source non vérifié · jsonld

Date publiée par l’employeur
2026-10-21
Première détection par notre source
2026-10-26
Mise à jour du dossier source
2026-11-05

Ces dates décrivent le dossier source, pas une vérification en direct du recrutement. Consultez l’offre originale.

Détails du poste

NiveauIntermédiaire
DomaineDonnées et analytique
Déplacementsavion : aucun · route : aucun
Milieu de travailBureau
PositionSurtout assis
Exigences physiquesphysique faible · ordinateur élevé
LanguesEnglish

Résumé et détails rédigés par l’IA à partir de l’offre; l’offre de l’employeur fait foi.

Postuler
ChampValeur
Offres sur Jobsy331
Description

Context Engine - GCP Data and graph engineer

Employment Type: Contract-to-Hire (possible 3-month CTH)

Location: Toronto, Ontario

Work Mode : Hybrid

Job Summary

Our client is looking for a highly skilled Data & Graph Engineer to build and fine-tune graph-driven data platforms, search infrastructure, and event-based data architectures. You'll bring strong graph modeling and query expertise, along with a solid grasp of search datastores, knowledge graphs, and cache/index invalidation. Together these will power fast, scalable data retrieval and analytics. You'll work alongside product, architecture, platform, and engineering teams to create intelligent data relationships, robust search capabilities, and real-time data flow across enterprise systems.

Key Responsibilities

• Model complex business domains and entity relationships as scalable graph structures.

• Write and tune graph queries using Cypher (Neo4j), and GraphQL where it applies.

• Build and maintain knowledge graphs and relationship-focused data platforms.

• Design and optimize search using Elasticsearch/OpenSearch, vector databases, and hybrid search approaches.

• Build pipelines that keep transactional, graph, and search systems in sync.

• Implement event-driven architectures for near real-time data updates.

• Design cache and index refresh logic, with event-driven invalidation, to keep distributed systems consistent.

• Work with application teams to shape search relevance, ranking, and retrieval strategies.

• Put monitoring, observability, and data quality checks in place across graph and search platforms.

• Improve query performance, indexing strategies, and data access patterns.

• Set up governance, lineage, and metadata management practices for the graph ecosystem.

Required Qualifications

• Strong expertise in graph data modeling and graph query languages, especially Cypher (Neo4j).

• Hands-on experience with search datastores such as Elasticsearch or OpenSearch.

• Experience building and managing knowledge graphs.

• A solid understanding of cache and index invalidation strategies for low-latency data retrieval.

• Experience with event-driven architectures and real-time data synchronization.

• The ability to collaborate effectively across product, architecture, platform, and engineering teams.

Nice to Have

• Experience designing knowledge graphs and ontologies.

• Background in recommendation engines or relationship analytics.

• Exposure to GenAI, RAG, and GraphRAG architectures.

• Experience integrating vector stores with graph databases.

• Familiarity with Kubernetes and cloud-native deployments.

• Infrastructure as Code experience (Terraform, CloudFormation).

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