Senior Data Engineer II - Time Data Engineering

Company Description 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 Description 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  will be responsible for delivering key infrastructure initiatives, setting the technical streaming strategy and 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…