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
