Wise is a global technology company, building the best way to move and manage the world’s money.
Min fees. Max ease. Full speed.
Whether people and businesses are sending money to another country, spending abroad, or making and receiving international payments, Wise is on a mission to make their lives easier and save them money.
As part of our team, you will be helping us create an entirely new network for the world's money.
For everyone, everywhere.
More about our mission and what we offer.
Job DescriptionWe 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.
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 have a direct and measurable impact across multiple Wise products by enabling dynamic, real-time capital positioning as one of the founding engineers of a high-visibility team, laying the groundwork today and scaling the full engineering capability over the next year.
At Wise, we operate in autonomous, cross-functional teams. You will work in a highly collaborative environment, partnering closely with Product Managers, Data Scientists, Quantitative Analysts, and Treasury Ops.
Engineering at Wise is founded on clear communication, healthy debate to reach technical clarity, and a deep consciousness of system edge cases and failure modes before code hits production.
What will you be working on?
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.
This is an opportunity to architect low-latency streaming pipelines that deliver instant, global liquidity visibility across every currency, jurisdiction, and nostro account.
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.
The squad operates with high ownership and low ego, thriving on clear, actionable communication that bridges the gap between complex streaming architecture and real-world Treasury impact.
Navigating high-stakes trade-offs across latency, financial cost, regulatory boundaries, and customer experience is second nature to us. This will give you the opportunity to proactively chase clarity using collaborative RFCs, whiteboard sessions, and direct stakeholder loops to solve ambiguity before it hits production.
Above all, we lead by example: writing well-tested, maintainable code, rigorous design reviews, and constantly raising the engineering bar together.
Qualifications
We are fully aware that it is uncommon for a candidate to have all skills required and we fully support everyone in learning new skills with us. So if you have some of those listed below and are eager to learn more we do want to hear from you!
Advanced Stream Processing & Event-Driven Architecture: Proven track record building, deploying, and operating production-grade, low-latency stream processing pipelines using Apache Kafka (or Kafka Streams, Flink, Spark Streaming).
Idempotency & Event Reliability: 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.
Real-Time Data Aggregation: Strong expertise in windowing techniques (tumbling, sliding, session windows), stateful stream processing, and high-throughput real-time aggregation across streaming data pipelines.
Streaming Data Modeling: 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).
Defensive Engineering & Failure Modes: You will instinctively design for dead-letter queues, backpressure management, circuit breakers, and state-store recovery.
Interested? Find out more:
How we work – a practical guide
DEI @ Wise
Wise Tech Stack (2025 update)
Our Engineering career map
Scaling our Infrastructure; how we make it work
Wise Engineering – https://medium.com/wise-engineering
What do we offer:
£111,000- £145,000 plus RSUs
Wise Benefits
For everyone, everywhere. We're people building money without borders — without judgement or prejudice, too. We believe teams are strongest when they are diverse, equitable and inclusive.
We're proud to have a truly international team, and we celebrate our differences.
Inclusive teams help us live our values and make sure every Wiser feels respected, empowered to contribute towards our mission and able to progress in their careers.
If you want to find out more about what it's like to work at Wise visit Wise.Jobs.
Keep up to date with life at Wise by following us on LinkedIn and Instagram.
Skills Required
- Proven experience building, deploying, and operating production-grade, low-latency stream processing pipelines using Apache Kafka, Kafka Streams, Apache Flink, or Apache Spark Streaming.
- Hands-on experience handling duplicate events, out-of-order processing, late-arriving data, and exactly-once processing semantics in financial or mission-critical systems.
- Expertise in windowing techniques, including tumbling, sliding, and session windows, stateful stream processing, and high-throughput real-time aggregation.
- Advanced experience modeling data for real-time stream consumers and analytical stores, including event schemas, state-store schemas, and schema evolution using Protobuf or Avro.
- Experience with defensive engineering practices, including dead-letter queues, backpressure management, circuit breakers, and state-store recovery.
Wise Compensation & Benefits Highlights
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Leave & Time Off Breadth — U.S. materials describe extensive paid leave (PTO, sick time, holidays, “Me Days,” volunteer and compassionate leave) plus a paid six‑week sabbatical after four years. Feedback suggests the time‑off package is a standout element of the offering.
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Parental & Family Support — Benefits information highlights up to 18 weeks of fully paid parental leave in many locations, with clear tenure qualifiers in some markets. Feedback suggests these policies are robust and a notable strength.
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Equity Value & Accessibility — Company and job-posting materials indicate RSUs are a regular part of compensation, with a shift toward RSUs since 2022. Feedback suggests the equity component is a relatively substantial part of total rewards.
Wise Insights
What We Do
Wise is a global technology company, building the best way to move and manage the world's money. With Wise Account and Wise Business, people and businesses can hold 40 currencies, move money between countries and spend money abroad. Large companies and banks use Wise technology too; an entirely new network for the world's money. Launched in 2011, Wise is one of the world’s fastest growing, profitable tech companies. In fiscal year 2025, Wise supported around 15.6 million people and businesses, processing over $185 billion in cross-border transactions and saving customers around $2.6 billion.
Why Work With Us
We’re truly global in who we are, how we work, and how we build. Everything we do is centred around creating a world of money that’s fast, easy, fair. And open to all. Everyone who works here owns a piece of Wise, from the work they do, to the stock they hold.
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Wise Offices
Hybrid Workspace
Employees engage in a combination of remote and on-site work.
We expect new joiners in the office most days to build connections and learn from colleagues for their first six months. After that, most Wisers split their working week between the office and home, typically coming in at least 12 times a month.
