Senior Data Engineer

Design and architect Bureau's cloud data lake and lakehouse, the single source of truth for identity signals, risk events, and decision outcomes across all our products

Build and operate scalable batch and streaming pipelines that ingest, clean, transform, and aggregate data from disparate sources, device SDKs, APIs, third-party data partners, and internal services

Develop and maintain orchestration workflows (Airflow) that power research, reporting, compliance analytics, and ML model training and feature pipelines

Own the reliability, observability, and cost-efficiency of production data infrastructure , with monitoring, alerting, and SLAs appropriate for a system that makes real-time risk decisions

Collaborate with data science and ML teams to design feature stores and data pipelines that shorten the path from raw signal to deployed model

Champion data engineering best practices, data quality, schema governance, testing, documentation, and mentor engineers across the team

Contribute to graph-based fraud intelligence: modeling identity networks and fraud rings using graph databases

Graph database experience (Neo4j, TigerGraph, Amazon Neptune); we use graph technology to uncover fraud networks and hidden identity linkages

Exposure to fraud detection, risk, identity, fintech, or other high-stakes real-time data domains

Experience with data quality frameworks, data cataloging, or lakehouse table formats (Iceberg, Delta Lake, Hudi)

Experience supporting ML platforms: feature stores, training pipelines, or model-serving data flows

We hire self-motivated people and get out of their way

We value performance, not hours worked

Speed, ownership, and impact matter most