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Senior Data Engineer I - Global KYC & Onboarding

London, United Kingdom

Live, first seen by us today
Pay
Pay not listed
Work setting
Not stated
Employment
Full-time — employment source
Employment type in the employer’s posting: Full-time
From the employer’s posting

What you’ll work on

Full posting
  • Design and maintain ETL/ELT pipelines ingesting high-volume verification event data

  • Model onboarding funnels, verification triggers and conversion metrics in analytical data models

  • Replace legacy verification data flows with modern, scalable pipelines

  • Optimise data-intensive workflows and queries to fix latency bottlenecks

  • Set shared data contracts, pipeline monitoring and automated testing standards

From the employer’s posting
Designing and maintaining robust ETL/ELT pipelines that ingest high-volume, event-driven data from verification services
Mapping complex transactional events into coherent, business-accurate data models
replace 8-year-old legacy verification infrastructure with modern, scalable data flows
Optimise data-intensive workflows and queries, resolving latency bottlenecks
define shared data contracts, pipeline monitoring best practices, and automated testing frameworks

What you’ll bring

All qualifications

Core experience

  • 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.
  • Hands-on experience with modern data transformation tools like dbt.
  • 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.
  • 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).
Qualification wording
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.
Hands-on experience with modern data transformation tools like dbt.
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.
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).
Apply at Wise

Posting record

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Status in our records
Live
First seen by us
Nov 7, 2026today
Recorded sightings
1
Reposted
once since Nov 2, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications. We count a repost when the same title and location comes back as a new listing within 60 days of the last one coming down. Some hiring systems expire listings on a schedule, so repost rates vary by system.

How this job compares

Time since we first saw it

Day 0

Early. Similar jobs usually come down between day 6 and day 54.

At Wise, jobs usually come down by about day 11.

From 11,508 similar postings that came down, and 338 of Wise’s. Coming down is not always a hire.

Wise is hiring

53 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Hiring at a steady pace
  • Takes jobs down quickly
  • 36% of open jobs were reposted
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • SQL
  • dbt
  • Kafka
  • Snowflake
  • Spark
  • Trino
  • Airflow
Where the posting names them
- 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.
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.
- 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.
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).
- 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).
- 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.

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Has Wise posted this job before?

Yes. We’ve followed one other Senior Data Engineer I - Global KYC & Onboarding job there since November 2026. It came down after 5 days.

  1. LondonCame down after 5 days, first seen Nov 2
  2. This jobUp 1 day so far, first seen Nov 7

Demand for Data Engineer roles

New Data Engineer postings at the employers we follow are up 8% over the last 5 weeks compared with the 5 before.

Weekly new Data Engineer postings at the same employers, from the week of August 17 to the week of October 26. The fewest in a week was 839, the most 1,314, and the latest week had 1,079.
August 17Last week

Each bar is one week of new postings. The darkest bars are the last 5 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under Data Engineer, by the work the posting describes.

Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.

Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.

An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.

US government figures for database architects

Median yearly pay, May 2025
$139,500
Expected change, 2025 to 2035
9.4% more jobsagainst 3.5% for all jobs

The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.

Job description

View original posting ↗

Job Description

We'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.

Qualifications

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).

Additional Information

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.

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.

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London, United Kingdom

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.
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