Staff Backend Graph Engineer

• Shape the graph. Define the schemas, relationships, and ontology that make identity data consistent and extensible.
• Own entity resolution at scale. Decide how records, people, devices, and addresses connect, and how confident we are, across data that is messy, sparse, and sometimes adversarial.
• Build for speed and volume. Design batch and real-time pipelines, low-latency APIs, and serving systems that hold up under heavy load.
• Power fraud intelligence. Ship the production systems behind our ML features, model inference, and graph analytics.
• Move the numbers. Improve performance, reliability, and cost, and prove it with measurements.
• Set the direction. Lead architecture decisions, document the tradeoffs, and carry initiatives from first design through production rollout.
• Raise the bar. Mentor engineers and set the standard for design reviews, testing, CI/CD, and operations.
• Protect identity data. Build privacy, security, and PII protection into every system from day one.
• Your toolkit:Java, Scala, or Python. Spark, Kafka, Flink, Airflow, and AWS, including EMR. Graph technologies like Neo4j and Amazon Neptune.

What You Will Bring

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, or related field
• 7+ years building and running distributed systems in the cloud, with at least 2 at Staff or Senior Staff scope, or the equivalent
• Production scale you can quantify. You can tell us what you built, how big it was, and how much you improved latency, reliability, or cost
• Deep Spark, Kafka, or Flink experience in both batch and streaming, including debugging them in production
• Low-latency serving. You have built and tuned APIs where milliseconds matter
• Graph or entity-resolution experience. You have modeled connected data, matched records across noisy sources, or built an identity graph. Fraud or identity verification is a strong plus
• Cloud and operations fluency. AWS, Kubernetes, infrastructure as code, CI/CD, and real production observability
• ML data pipelines on Databricks, SageMaker, or similar, plus orchestration with Airflow or equivalent
• Technical leadership. You have led ambiguous, cross-team work, mentored engineers, and changed the direction of a system through design docs and influence, not authority

What This Job is Not

• It’s not a role for someone who hasn’t owned a system end to end in production, including being on call for it.
• It’s not feature work on platforms someone else designed.
• It’s not a defined backlog. You’ll frame ambiguous problems yourself.
• It’s not a place to treat data privacy as a compliance checkbox.

Socure is an equal opportunity employer that values diversity in all its forms within our company. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
If you need an accommodation during any stage of the application or hiring process—including interview or onboarding support—please reach out to your Socure recruiting partner directly.

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