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Senior Data Engineer I

  • Hybrid
  • 6+ years

Salary

Not stated

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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 the company Platform Verification (our B2B the company-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 the company 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.

Requirements

  • 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.
  • 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 the company visit the company's site .
  • Keep up to date with life at the company 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 the company visit the company's site .
  • Keep up to date with life at the company by following us on LinkedIn and Instagram .
  • Company Description
  • The company 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, the company 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 .

Where you’d work

Part of the week in the office

You can work from

  • United Kingdom

About the company

Company hidden

  • Industry: FinTech

Office in London, United Kingdom

Your chances

Likely still hiring, not crowded yet, and you'd be among the first.

  • 15 checks run
  • 6 good signs
  • 1 red flag

Still hiring?

10 checks

Likely active

In its favour2

  • Still on the company's own careers site, checked 1 h agoModerate evidence
  • Found in the last 48 hours, before the big job boardsModerate evidence

Against it1

  • Listed again after an earlier listing of the same role closedModerate evidence

How crowded?

5 checks

Low

In its favour4

  • In its Early Window: not on the big job boards yetStrong evidence
  • Hybrid in London: only people nearby can take itSlight evidence
  • Senior level: far fewer people qualifySlight evidence
1 moreFewer
  • Asks for Airflow, which only 1% of open roles doSlight evidence

Fits Me

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Details13 facts · Role, Location, Compensation, Employment, Company
Tech stack
  • Python
  • SQL
  • dbt
  • Kafka
  • Spark
  • Snowflake
  • Airflow
Seniority
Senior
Type
Full-time
Industry
FinTech
Specialty
Data Engineering
Region
United Kingdom
Show 7 more factsShow less

Role

Category
Data & Analytics
Specialty
Data Engineering
Seniority
Senior
Experience
6+ years
Tech stack
  • Python
  • SQL
  • dbt
  • Kafka
  • Spark
  • Snowflake
  • Airflow

Location

Work model
Hybrid
Region
United Kingdom
Office
  • London, United Kingdom
Remote from
  • United Kingdom

Compensation

Salary
Salary by agreement
Pay period
Annual

Employment

Type
Full-time

Company

Industry
FinTech

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