Backend Engineer, Feature Platform

What you'll do

• Build and maintain high-performance infrastructure to process millions of events with low latency.
• Design and implement complex feature topologies including graphs, support vectors, and time-series data.
• Centralize risk logic from various teams into a single governed feature engineering platform.
• Develop automated controls and machine learning features for fraud, AML, and risk detection.
• Manage the full lifecycle of data points from discovery and experimentation to production use.
• Expand self-service capabilities to improve internal tool adoption across different business units.
• Solve complex technical challenges related to distributed microservices and large-scale data pipelines.
• Identify impactful problems and drive end-to-end solutions based on data-driven decisions.

What we're looking for

• 3+ years of Java 11+ knowledge and fluency in Java 21+.
• Familiarity with Python or willingness to learn it on the job.
• Experience with batch or stream processing, preferably using Apache Spark and Flink/Kafka streams.
• Familiarity with SQL and no-SQL (document) databases.
• Experience with complex systems distributed across microservices, Kafka, scattered data, and ownership.
• Hands-on knowledge of system integration patterns.
• A strong product mindset to prioritize customer experience and make data-driven decisions.
• Data Engineering background, including large-scale pipelines, feature engineering, graph algorithms, or Apache Iceberg/Trino (preferred).