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're looking for an experienced Senior Data Engineer to join our Global KYC & Onboarding squad within the FinCrime organisation. You will be instrumental in designing and building the data pipelines, storage infrastructure, and analytical data models that power customer onboarding and financial crime controls across the globe.
This role sits directly between core engineering microservices and product analytics. While customer-facing systems fire dozens of raw operational events per verification flow, our analytics and machine learning teams require structured, clean, and reliable metrics to steer the business. You will own the data journey between these two worlds, transforming high-volume operational events into observable, audit-ready analytical datasets.
Operating across our squad's three core pillars—Business Onboarding Verification, Personal Onboarding Verification, and Wise Platform Verification (our B2B Wise-as-a-Service solution)—you will be the driving force behind modernising our verification data ecosystem, focusing on:
- Data Ingestion & Pipelines: Designing and maintaining robust ETL/ELT pipelines that ingest high-volume, event-driven data from verification services and transform it into reliable analytical stores.
- Domain Data Modelling: Mapping complex transactional events into coherent, business-accurate data models that define how customer onboarding funnels, verification triggers, and conversion metrics are tracked.
- Platform Modernisation: Collaborating with software engineering to replace 8-year-old legacy verification infrastructure with modern, scalable data flows built for true "config-change" flexibility.
- Observability & Auditability: Ensuring that every onboarding flow and FinCrime control is measurable, auditable, and transparent out-of-the-box for regulatory compliance and product health monitoring.
What will you be working on?
You will join the squad at an exciting inflection point. We were the first team at Wise to establish dedicated data engineering, and you’ll join our team of data engineers to scale and professionalise this foundational capability across the entire verification domain.
The core challenge for the team—and your immediate focus—is modernising our data layer while the squad delivers the new Onboarding Platform. We don't hide away for two years to build a finished product; we ship iteratively, learn, and replace legacy components in place. You will ensure that as new platform capabilities go live, our data models, pipelines, and reporting layers scale seamlessly alongside them.
Your immediate impact will be to:
- Bridge Engineering & Analytics: Translate raw system inputs into clean, aggregated data models that empower Product Analysts and Data Scientists to measure KPIs, conversion funnels, and control pass rates without having to untangle backend service logs.
- Modernise Verification Data Architecture: Build and standardise production pipelines in Python and Airflow, replacing ad-hoc queries and fragmented scripts with robust, automated data infrastructure.
- Improve Performance & Scale: Optimise data-intensive workflows and queries, resolving latency bottlenecks and ensuring data consistency across personal, business, and platform onboarding spaces.
- Set Data Engineering Standards: Partner with engineering, analytics, and compliance to define shared data contracts, pipeline monitoring best practices, and automated testing frameworks across the squad.
What do you need?
- Strong Python Fundamentals: Solid software engineering skills in Python with the ability to write clean, maintainable code, navigate complex algorithms, and optimize data-intensive tasks for performance and computational efficiency.
- Advanced SQL & Data Modelling: Extensive experience designing normalized and dimensional data models, paired with strong proficiency in crafting, debugging, and tuning complex SQL queries over large-scale datasets.
- Pipeline & Workflow Orchestration: Proven track record building, scheduling, and monitoring production pipelines using modern workflow orchestrators such as Apache Airflow.
- Systems & Data Architecture Mindset: Experience handling high-throughput event data and a deep understanding of analytical databases, storage formats, and execution plans.
- Ownership & Pragmatic Autonomy: Comfortable working in an evolving domain, taking vague or cross-functional problems from raw concept through to production implementation without hand-holding.
- Collaborative Partner: Proven ability to communicate effectively across boundaries—collaborating closely with Software Engineers, Data Scientists, Product Analysts, and operational stakeholders to align on contracts and schemas.
Nice to Have:
- Hands-on experience with modern data transformation tools like dbt.
- Familiarity with distributed compute and storage platforms (e.g., Kafka, Spark, Snowflake, or Presto/Trino).
- Experience in product-led SaaS, fintech, or high-growth tech environments navigating complex event tracking or onboarding funnels (prior FinCrime or KYC experience is not required).
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.
#LI-AB3 #LI-Hybrid
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
- Strong Python fundamentals and software engineering skills, including maintainable code, algorithmic reasoning, and performance optimization.
- Extensive experience with advanced SQL and normalized and dimensional data modeling.
- Experience building, scheduling, and monitoring production pipelines with workflow orchestrators such as Apache Airflow.
- Experience handling high-throughput event data and understanding analytical databases, storage formats, and execution plans.
- Ability to independently take ambiguous, cross-functional problems from concept through production implementation.
- Effective collaboration with software engineers, data scientists, product analysts, and operational stakeholders.
- Hands-on experience with modern data transformation tools such as dbt.
- Familiarity with distributed compute and storage platforms such as Kafka, Spark, Snowflake, or Presto/Trino.
- Experience in product-led SaaS, fintech, or high-growth technology environments involving event tracking or onboarding funnels.
Wise Compensation & Benefits Highlights
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Leave & Time Off Breadth — Benefits information highlights generous paid time off, with added elements like sabbaticals and personal days in some locations. Feedback suggests time away from work is a notable strength.
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Healthcare Strength — Benefits materials indicate comprehensive medical, dental, and vision coverage. Feedback suggests the health plans are generally well regarded.
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Equity Value & Accessibility — Company materials emphasize RSUs offered to employees, enabling participation in longer‑term company performance. Feedback suggests equity is a meaningful component 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.
