Senior Data Engineer II - Real Time Data Engineering
Wise · London, England ·
Overview
In this role, you will design and build the foundations of Wise’s real-time liquidity observability and streaming data pipelines to support global treasury operations. You’ll work within the Treasury Global Liquidity team to enable dynamic, intraday capital positioning and high-visibility liquidity across currencies and nostro accounts.
You will implement robust, scalable streaming architectures and collaborate with product, data science, and treasury teams to drive measurable impact. This is a high-ownership role with significant scope to shape the engineering approach and performance of critical liquidity systems.
Pay / Benefits
- RSUs
- Wise Benefits
Responsibilities
- Architect and deliver high-throughput streaming pipelines (Kafka, Flink) powering real-time liquidity visibility
- Build and operate robust, low-latency data infrastructure for global financial transactions
- Modernize liquidity attribution with real-time models and event-driven data flows
- Ensure system reliability with idempotent, exactly-once processing and strong failure-mode handling
- Collaborate with cross-functional teams to translate business needs into scalable streaming solutions
- Champion testing, design reviews, and incident readiness to raise engineering standards
- Support schema evolution and analytics-ready data models for downstream stores
Key requirements
- Advanced stream processing experience with production-grade pipelines (Kafka, Kafka Streams, Flink, Spark Streaming)
- Experience with idempotency, out-of-order handling, late-arriving data, and exactly-once semantics in financial domains
- Real-time data aggregation, windowing, and stateful stream processing
- Streaming data modeling for event schemas and analytics stores (Protobuf/Avro, schema evolution)
- Defensive engineering mindset (dead-letter queues, backpressure, circuit breakers, state-store recovery)
- collaboration
- clear communication
- ownership
- Apache Kafka
- Kafka Streams
- Flink
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