Senior Data Engineer II – Real Time Data Engineering- Java

Overview

In this role you will build and scale the real-time liquidity observability stack and streaming data pipelines to support Wise’s global treasury operations. You’ll work with cross-functional teams to enable immediate visibility into capital positioning and high-velocity financial movements. You will help shape the streaming architecture and tooling, balancing latency, cost, and reliability to support global liquidity across currencies and accounts. This is a high-impact, foundational role with clear ownership and collaboration across product, data science, and treasury operations.

Pay / Benefits

• RSUs
• Wise Benefits

Responsibilities

• Design and build high-throughput streaming pipelines using Kafka and Flink
• Develop real-time liquidity attribution and visibility across multiple currencies and accounts
• Ensure robust, low-latency architectures with fault tolerance and failure modes handling
• Collaborate with Product, Data Science, and Treasury Ops to translate business needs into scalable data infrastructure
• Implement and maintain data models and schemas (Protobuf/Avro) for streaming and analytical stores
• Address data quality, idempotency, schema evolution, and operator reliability (DLQs, backpressure, circuit breakers)
• Drive technical RFCs, design reviews and contribute to a culture of tested, maintainable code
• Balance latency, cost, regulatory constraints, and user experience in streaming solutions

Key requirements

• Proficiency in JAVA or Scala
• Experience with production-grade stream processing: Kafka, Kafka Streams, Flink, or Spark Streaming
• Strong background in idempotent and exactly-once processing, handling out-of-order events
• Real-time data aggregation and windowing techniques
• Streaming data modeling for real-time and analytical stores (Protobuf/Avro)
• Defensive engineering: DLQs, backpressure, circuit breakers, state-store recovery

• Collaborative mindset in cross-functional teams
• Clear and constructive communication
• Ability to navigate ambiguous requirements with RFCs and whiteboard sessions
• Apache Kafka
• Kafka Streams / Flink / Spark Streaming
• Protobuf / Avro schemas and evolution

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