Context Engineer - Data and graph engineer

We are seeking a highly skilled Data & Graph Engineer to design, build, and optimize graph-based data platforms, search infrastructures, and event-driven data architectures. The ideal candidate will have expertise in graph data modeling, graph query languages, search datastores, knowledge graphs, and cache/index invalidation strategies to support scalable, low-latency data retrieval and analytics solutions.

This role requires close collaboration with product, architecture, platform, and engineering teams to build intelligent data relationships, search capabilities, and real-time data propagation mechanisms across enterprise systems.

Key Responsibilities

• Design and implement scalable graph data models for complex business domains and entity relationships.
• Develop and optimize graph queries using technologies such as:
• Cypher (Neo4j)
• GraphQL (where applicable)
• Build and maintain knowledge graph and relationship-centric data platforms.
• Design and optimize search solutions leveraging:
• Elasticsearch / OpenSearch
• Vector databases and hybrid search architectures
• Create data pipelines that synchronize transactional, graph, and search systems.
• Implement event-driven architectures for near real-time data updates and synchronization.
• Design cache/index refresh and event-driven invalidation mechanisms to ensure data consistency across distributed systems.
• Partner with application teams to define search relevance, ranking, and retrieval strategies.
• Develop monitoring, observability, and data quality controls across graph and search platforms.
• Improve query performance, indexing strategies, and data access patterns.
• Establish governance, lineage, and metadata management practices for graph ecosystems.

Preferred Skills

• Knowledge graph and ontology design experience.
• Experience with recommendation engines or relationship analytics.
• Exposure to GenAI, Retrieval-Augmented Generation (RAG), and GraphRAG architectures.
• Experience integrating vector stores and graph databases.
• Familiarity with Kubernetes and cloud-native deployments.
• Infrastructure as Code (Terraform, CloudFormation).