Senior Data Engineer I - Global KYC & Onboarding

Description

The company is hiring a senior data engineer for its Global KYC & Onboarding squad, which sits in the FinCrime organisation.

The role sits between core engineering microservices and product analytics. You will turn high-volume operational events from verification flows into structured, clean and reliable datasets for analytics and machine learning teams.

The squad covers 3 core pillars: business onboarding verification, personal onboarding verification, and platform verification for the company's B2B-as-a-service offering.

The squad is replacing its 8-year-old legacy verification infrastructure while it builds the new Onboarding Platform. It ships in small steps and swaps legacy parts in place rather than waiting 2 years for a finished product.

The company was the first team to set up dedicated data engineering, and you will join its data engineers in extending that work across the verification domain.

Responsibilities

• Design and maintain ETL/ELT pipelines that bring high-volume, event-driven verification data into reliable analytical stores.
• Map complex transactional events into accurate business data models that track onboarding funnels, verification triggers and conversion metrics.
• Work with software engineers to replace legacy verification infrastructure with scalable data flows that support flexible config changes.
• Make every onboarding flow and FinCrime control measurable, auditable and transparent by default, for regulatory and product health monitoring.
• Turn raw system inputs into aggregated models so analysts and data scientists can measure KPIs, funnels and control pass rates without reading backend logs.
• Build and standardise production pipelines in Python and Airflow, replacing ad-hoc queries and fragmented scripts.
• Optimise data-heavy workflows and queries, remove latency bottlenecks, and keep data consistent across personal, business and platform onboarding.
• Work with engineering, analytics and compliance to set shared data contracts, pipeline monitoring practices and automated testing across the squad.
• Make sure data models, pipelines and reporting layers scale alongside new platform features as they go live.

Requirements

• Strong Python skills: clean, maintainable code, complex algorithms and performance-efficient data tasks.
• Extensive experience with normalised and dimensional data models, and with writing, debugging and tuning complex SQL on large datasets.
• Proven record of building, scheduling and monitoring production pipelines with orchestrators such as Apache Airflow.
• Experience with high-throughput event data and a solid understanding of analytical databases, storage formats and execution plans.
• Comfortable taking vague or cross-functional problems from concept to production without close guidance.
• Able to communicate across boundaries with software engineers, data scientists, product analysts and operational stakeholders, aligning on contracts and schemas.
• Hands-on experience with dbt.
• Familiarity with distributed compute and storage platforms such as Kafka, Spark, Snowflake or Presto/Trino.
• Background in product-led SaaS, fintech or high-growth tech, working with event tracking or onboarding funnels. FinCrime or KYC experience is not required.

Conditions

Hybrid working model.

The company welcomes applicants from every background and values diverse, equitable and inclusive teams.