socure - 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. • 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.