Senior Data Engineer II - Real Time Data Engineering

Description

The company is hiring a senior data engineer for its Treasury Global Liquidity team, working on the foundations of a real-time liquidity observability stack and core streaming data pipelines that support global financial operations.

You will set the streaming technical direction and deliver core infrastructure, building scalable systems that process fast-moving financial flows where errors are not tolerated. The work has measurable impact across several products, helping treasury decide capital positioning in real time.

You will be one of the founding engineers of a highly visible team. The first phase is laying the groundwork, with the full engineering capability scaled up over the following year.

The company runs autonomous, cross-functional teams. You will collaborate closely with Product Managers, Data Scientists, Quantitative Analysts and Treasury Ops.

Engineering culture values clear communication, productive debate to reach technical clarity, and careful thinking about edge cases and failure modes before code reaches production.

The team operates with high ownership and little ego, communicating clearly and actionably to connect streaming architecture with treasury outcomes.

Responsibilities

• Design and build high-throughput Kafka and Flink streaming pipelines that process global bank transactions and balance demand against supply intraday.
• Help develop the real-time Liquidity Attribution Model (LAM).
• Build low-latency pipelines that give instant, global liquidity visibility across every currency, jurisdiction and nostro account.
• Build the engine behind cash positioning, routing high-value transactions instantly with fine-grained event controls.
• Support ML forecasting models that aim to maximise yield on surplus capital.
• Harden the event architecture against out-of-order spikes, network partitions and schema changes.
• Work with a Medallion architecture and pair streaming pipelines with sub-second OLAP queries, giving Treasury Ops instant, precise visibility into unencumbered liquidity before end of day.
• Make trade-offs across latency, financial cost, regulatory boundaries and customer experience.
• Resolve ambiguity through RFCs, whiteboard sessions and direct stakeholder discussions before problems reach production.
• Write well-tested, maintainable code, take part in rigorous design reviews and help raise the engineering bar across the team.

Requirements

• The company knows few candidates match every skill listed. If you meet some of these and want to learn the rest, it wants to hear from you.
• Proven experience building, deploying and running production low-latency stream processing pipelines with Apache Kafka, Kafka Streams, Flink or Spark Streaming.
• Deep hands-on experience handling duplicate events, out-of-order and late-arriving data, and exactly-once processing in financial or mission-critical systems.
• Strong skills in windowing (tumbling, sliding, session), stateful stream processing and high-throughput real-time aggregation.
• Advanced experience modelling data for stream consumers and downstream analytical stores, including event schemas, state store schemas and schema evolution with Protobuf or Avro.
• You design by default for dead-letter queues, backpressure, circuit breakers and state store recovery.

Conditions

Base salary of £111,000 to £145,000, plus RSUs.

Equal-opportunity statement: the company welcomes diverse candidates and does not tolerate judgement or prejudice.

The company describes itself as a global technology company that builds ways to move and manage the world's money, with a team spread across countries.

Benefits

• Access to the company Benefits.
• Restricted stock units (RSUs) on top of salary.