Data Lead (Financial Crime)

Data Science Jobs UK; Greater London; Hybrid; GBP 100,000 - 120,000; Full time

Job summary

Data Science Jobs UK is seeking a Financial Crime Data Lead in Central London on a hybrid basis. The role is permanent with a salary up to £120k pa plus bonus. You will design and build a new enterprise-wide Financial Crime data platform supporting KYC, AML, and risk processes.

The candidate will lead data engineering, data architecture and governance efforts, integrating multiple systems and data sources to enable reporting, controls and AI-enabled decision making.

Qualifications

• Strong SQL and Python experience.
• Commercial Snowflake experience (or equivalent modern cloud data platform).
• Data Engineering, Data Architecture or Data Product leadership background.
• Experience building complex integrations, APIs and data pipelines.

Responsibilities

• Design and deliver the Financial Crime data platform and canonical data model.
• Integrate data from onboarding, CRM, screening, monitoring and compliance systems.
• Build and maintain scalable data pipelines using modern cloud technologies.
• Develop trusted datasets supporting KYC, AML, transaction monitoring and risk processes.
• Implement data quality, lineage, governance and reconciliation controls.
• Create MI and reporting solutions that provide visibility of alerts, investigations, risk trends and operational performance.
• Support future AI and automation initiatives through AI-ready data products.
• Partner with Compliance, Risk, Operations and Technology teams to define and deliver data requirements.
• Establish data engineering standards, documentation and governance frameworks.

Skills

SQL

Python

Data engineering

Data architecture

Data governance

Tools

Snowflake

dbt

Airflow

Azure Data Factory

Dagster

Job description

Financial Crime Data Lead

Hybrid: Central London 2 days a week in the office

Permanent

Salary £100,000 - £120,000 pa

Paying up to £120k + Bonus

Posted 1 Sep 2026 (Last week)

We are currently working with a leading organisation undergoing a major transformation of its Financial Crime, Risk and Compliance technology landscape.

As part of this journey, they are looking to hire a Financial Crime Data Lead to play a central role in designing and building a new enterprise-wide Financial Crime data platform that will underpin key capabilities including transaction monitoring, client screening, onboarding, risk assessment and future AI-driven decision making.

The Role

• Data Engineering
• Financial Crime
• Data Architecture
• Governance
• AI Enablement

You’ll be responsible for creating a trusted Financial Crime data layer that brings together multiple systems and data sources into a single foundation supporting reporting, controls, workflow automation and analytics.

Key Responsibilities

• Design and deliver the Financial Crime data platform and canonical data model
• Integrate data from onboarding, CRM, screening, monitoring and compliance systems
• Build and maintain scalable data pipelines using modern cloud technologies
• Develop trusted datasets supporting KYC, AML, transaction monitoring and risk processes
• Implement data quality, lineage, governance and reconciliation controls
• Create MI and reporting solutions that provide visibility of alerts, investigations, risk trends and operational performance
• Support future AI and automation initiatives through AI-ready data products
• Partner with Compliance, Risk, Operations and Technology teams to define and deliver data requirements
• Establish data engineering standards, documentation and governance frameworks

Key Skills & Experience

• Strong SQL and Python experience
• Commercial Snowflake experience (or equivalent modern cloud data platform)
• Data Engineering, Data Architecture or Data Product leadership background
• Experience building complex integrations, APIs and data pipelines

Financial Crime Experience Including Areas Such As

• KYC
• AML
• Transaction Monitoring
• Screening
• Risk Ratings
• Compliance Case Management
• Strong data governance, lineage and data quality experience
• Experience with dbt, Airflow, Azure Data Factory, Dagster or similar tooling
• CI/CD, Git and modern engineering practices
• Strong stakeholder engagement and communication skills