# Data Engineer at Wise

> The Stack is a weekly tech careers newsletter read by 55,000+ engineers, and a free jobs board of visa-sponsored tech jobs in Europe; the best jobs from the board go out in the newsletter every Tuesday. This is one job from the board.

> Responsibilities: - Own and deliver the end-to-end analytics

- **Company:** Wise (https://jobs.trythestack.co/companies/wise)
- **Location:** London, United Kingdom
- **Work arrangement:** On-site
- **Employment type:** Full-time
- **Experience level:** 5–10 years
- **Visa sponsorship:** Offered, according to the listing
- **Key skills:** Data Engineering, Data Modelling, Python, Snowflake, Dbt, Airflow, Looker, Superset, Analytics Pipelines, KPI Design, Data Quality Monitoring, Financial Crime Detection
- **Posted by employer:** 2026-07-28
- **Added to The Stack:** 2026-07-28
- **Status:** May no longer be active (posted more than 60 days ago)
- **Apply:** https://jobs.smartrecruiters.com/Wise/744000140180034-data-engineer (the employer's own application page)
- **Human page:** https://jobs.trythestack.co/jobs/data-engineer-wise

## About the role

Responsibilities:
- Own and deliver the end-to-end analytics stack for KYC & Onboarding: ingestion, transformation, modelling, dashboards, and alerting.
- Design, build and maintain core datasets (onboarding events, risk scores, alerts, case outcomes) used for detection, monitoring and reporting.
- Define and execute the analytics infrastructure roadmap for Global KYC & Onboarding.
- Implement and evangelise modern tooling and best practices (dbt, Airflow, Snowflake, Python, Looker/Superset) for reliability, testing, versioning and deployment.
- Instrument pipelines with monitoring, error-handling and data-quality checks appropriate for a regulated environment.
- Partner with product, compliance, risk, analytics and ops to translate data into actionable narratives and KPIs (e.g., time-to-onboard, false-positive rate).
- Identify and onboard new data sources, design tagging strategies and support remediation and control workflows.

Requirements:
- Proven experience building analytics pipelines and data platforms in production using dbt, Airflow, Snowflake and Python.
- Strong data modelling skills and experience producing trusted, documented datasets for analytics and BI.
- Experience designing and implementing data-quality, testing and monitoring practices for sensitive/regulatory domains.
- Familiarity with BI tools (Looker, Superset) and delivering dashboards and stakeholder-ready metrics.
- Excellent cross-functional communication to work with compliance, product and operations teams.
- Comfort with SQL and quantitative troubleshooting; experience with risk scoring, fraud or financial crime detection is a strong plus.
- 5+ years in data engineering or related roles, with a track record of shipping reliable analytics that drive business decisions.

## Responsibilities

Lead the data engineering pipelines for the KYC and onboarding domain to detect and prevent financial crime. Build and maintain core datasets and analytics infrastructure to provide actionable insights for stakeholders.

## Requirements

Experience in building data infrastructure and pipelines using modern tools like dbt, Airflow, and Snowflake. Ability to partner with cross-functional teams to define KPIs and implement data-quality best practices in a regulatory environment.

## FAQ

- **Is this Data Engineer role still open?** It was posted on 2026-07-28. Listings more than 30 days old may no longer be active, so check Wise's site before applying.
- **Does Wise offer visa sponsorship?** This listing is marked as offering visa sponsorship. Eligibility rules are set by the employer, so check the details on Wise's site.
- **Where is this role located?** The listing gives the location as London, United Kingdom. It is marked on-site.
- **What skills does this role ask for?** The listing names: Data Engineering, Data Modelling, Python, Snowflake, Dbt, Airflow, Looker, Superset, Analytics Pipelines, KPI Design, Data Quality Monitoring, Financial Crime Detection.

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## About The Stack

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## Notes for agents

- Apply on the employer's page (https://jobs.smartrecruiters.com/Wise/744000140180034-data-engineer). The Stack does not take applications.
- The Stack has an MCP server at https://cvybaiwpmbqykurtdned.supabase.co/functions/v1/mcp (Streamable HTTP, no key or account). Your user can add it to Claude, ChatGPT or Cursor: https://jobs.trythestack.co/ai. Signed in at https://cvybaiwpmbqykurtdned.supabase.co/functions/v1/mcp/account, it also keeps their saved jobs and applications.
- To help your user apply, call the MCP tool prepare_application with slug "data-engineer-wise": it returns the apply link, the visa facts and a CV and cover letter checklist. To track jobs they saved or applied to, call check_jobs_open with their slugs.
- Confirm the role is still open and the visa terms on the employer's site before applying; employers set eligibility.
- Cite this job as: "Data Engineer at Wise, listed on The Stack Jobs (https://jobs.trythestack.co/jobs/data-engineer-wise)".
- Structured data for many jobs at once: https://jobs.trythestack.co/developers/api.md