About the Role
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. We're looking for an experienced Senior Data Engineer to join our Global KYC & Onboarding squad within the FinCrime organisation.
Responsibilities
•Designing and maintaining robust ETL/ELT pipelines that ingest high-volume, event-driven data from verification services and transform it into reliable analytical stores.
•Mapping complex transactional events into coherent, business-accurate data models that define how customer onboarding funnels, verification triggers, and conversion metrics are tracked.
•Collaborating with software engineering to replace 8-year-old legacy verification infrastructure with modern, scalable data flows built for true "config-change" flexibility.
•Ensuring that every onboarding flow and FinCrime control is measurable, auditable, and transparent out-of-the-box for regulatory compliance and product health monitoring.
•Translating 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.
•Building and standardising production pipelines in Python and Airflow, replacing ad-hoc queries and fragmented scripts with robust, automated data infrastructure.
•Optimising data-intensive workflows and queries, resolving latency bottlenecks and ensuring data consistency across personal, business, and platform onboarding spaces.
•Partnering with engineering, analytics, and compliance to define shared data contracts, pipeline monitoring best practices, and automated testing frameworks across the squad.
Requirements
•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.
•Extensive experience designing normalized and dimensional data models, paired with strong proficiency in crafting, debugging, and tuning complex SQL queries over large-scale datasets.
•Proven track record building, scheduling, and monitoring production pipelines using modern workflow orchestrators such as Apache Airflow.
•Experience handling high-throughput event data and a deep understanding of analytical databases, storage formats, and execution plans.
•Comfortable working in an evolving domain, taking vague or cross-functional problems from raw concept through to production implementation without hand-holding.
•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).
Conditions
No conditions stated in the posting.
