Staff Backend Graph Engineer

Role overview

Set technical direction for a large-scale identity graph that connects signals such as names, addresses, devices, email addresses, and phone numbers. The platform supports real-time identity decisions, so the work combines graph modeling and entity resolution with high-volume data processing and low-latency serving. You will lead ambiguous initiatives from architecture through production and take responsibility for systems in operation.

Responsibilities - Define schemas, relationships, and shared data concepts so identity information remains consistent and extensible. - Build entity-resolution systems that connect records across incomplete, noisy, or adversarial data and represent confidence in those matches. - Design batch and streaming pipelines, low-latency APIs, and serving systems that meet demanding throughput requirements. - Deliver production systems for machine learning features, model inference, and graph analytics. - Measure and improve performance, reliability, and operating cost. - Lead architecture decisions, document tradeoffs, guide initiatives through rollout, and mentor engineers on design, testing, delivery, and operations. - Build privacy, security, and protection for personal data into system design.

Requirements - Bachelor’s or master’s degree in computer science, data engineering, or a related field. - At least seven years building and operating distributed cloud systems, including two years at staff or senior staff scope, or equivalent experience. - A record of owning production systems end to end, with measurable scale and results for latency, reliability, or cost. - Deep production experience with Spark, Kafka, or Flink across batch and streaming workloads. - Experience building and tuning APIs where low response times matter. - Cloud operations experience with AWS, Kubernetes, infrastructure as code, CI/CD, and production observability. - Experience with machine learning data pipelines and workflow orchestration, such as Databricks or SageMaker with Airflow or an equivalent. - Technical leadership across ambiguous, cross-team work, including mentoring and influencing system direction through design documentation.

Nice to have - Experience modeling graph data, matching records across noisy sources, or building identity graphs; fraud detection or identity verification experience is especially relevant. - Familiarity with graph platforms such as Neo4j or Amazon Neptune, and programming in Java, Scala, or Python.