Data engineer in real time

Описание:

Wise is a global technology company, building the best way to move and manage the world’s money. We are looking for a passionate Senior Data Engineer II to join our Treasury Global Liquidity team. In this role, you will help design and build the foundations of our real-time liquidity observability stack and core streaming data pipelines that power global financial operations at Wise.

Задачи:

You will help design and build the foundations of our real-time liquidity observability stack and core streaming data pipelines that power global financial operations at Wise. You will be responsible for delivering key infrastructure initiatives, setting the technical streaming strategyand building robust, scalable systems that handle high-velocity financial movement with zero room for error.

You will transform the financial engineering impact by pioneering our real-time Liquidity Attribution Model (LAM)! You will architect high-throughput Kafka and Flink streaming pipelines that continuously process global bank transactions, dynamically balancing demand against supply intraday.

You'll build the high-octane engine behind our cash positioning, routing high-value transactions instantaneously with fine-grained event controls, fueling ML forecasting models to maximize yield on surplus capital, and bulletproofing our event architecture against out-of-order spikes, network partitions, and schema shifts.

You will also master a cutting-edge Medallion architecture and pairing streaming pipelines with sub-second OLAP querying, empowering Treasury Ops with instant, precise visibility into unencumbered liquidity redefining how global treasury operates at scale long before end-of-day.

Требования:

Proven track record building, deploying, and operating production-grade, low-latency stream processing pipelines using Apache Kafka (or Kafka Streams, Flink, Spark Streaming). Deep hands-on experience handling duplicate events, out-of-order log processing, late-arriving data, and exactly-once processing semantics in financial or mission-critical domains.

Strong expertise in windowing techniques (tumbling, sliding, session windows), stateful stream processing, and high-throughput real-time aggregation across streaming data pipelines. Advanced experience in modeling data for both real-time stream consumer patterns and downstream analytical stores (e.g., event schemas, state store schemas, schema evolution with Protobuf/Avro).

You will instinctively design for dead-letter queues, backpressure management, circuit breakers, and state-store recovery.

Условия:

£111,000- £145,000 plus RSUs

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