Graph and Data Engineer

About the role

This role builds a canonical entity and knowledge graph across Intelligence Core connectors to resolve identities (people, agents, systems, data entities). The entity layer supports data classification at the source to unify transaction reporting and underpins security, authority models, and external commerce credentials.

Key responsibilities

• Lead the classify‑at‑source pilot with Finance and Compliance to establish unified tag models and metrics.
• Build entity resolution pipelines across internal systems (Slack, Jira, Ironclad) using privacy‑preserving linkage and canonical IDs.
• Develop graph‑based correlation skills and establish verifiable baseline metrics for operational throughput and SAR false positives.
• Define graph architecture, governing schemas, temporal permissions, and provenance tracking to ensure full auditability.
• Maintain data accuracy using bitemporal modeling, automated drift detection, and historical replay capabilities for compliance.

Required profile

• Direct experience with entity resolution, identity systems or knowledge‑graph modelling.
• Strong Python skills plus production‑grade graph or relational data engineering.
• Applied ML for large‑scale resolution, including embedding‑ and LLM‑based matching, with rigorous benchmarking on synthetic or de‑identified data.
• Experience designing schemas and APIs for heterogeneous human and machine consumers.
• Comfort working directly with Finance and Compliance on live data pilots.

Required skills

• Python
• Graph data engineering
• Relational data engineering
• Applied machine learning (embeddings, LLMs)
• Schema and API design
• Bitemporal modeling

What we offer

• Healthcare insurance covering ~100% of employee premiums (U.S. only)
• Vision & Dental insurance (U.S. only)
• Equity participation
• Maternity & Paternity leave after 6 months
• WeWork All Access Membership
• Remote work stipend and learning & development stipend after 6 months