Financial Crime Data Engineering Lead (snowflake, dbt)

You will own and shape the financial crime data platform, delivering robust Snowflake and dbt-driven data infrastructure to support AML, KYC, screening and related operations. You work hands-on with data engineering while setting technical direction and standards for the team. You’ll connect data across transactional monitoring, CRM and governance systems to improve data quality, reporting and future AI capabilities. This role blends architectural ownership with practical delivery in a regulated, enterprise environment.

• bonus
• pension
• hybrid working
• up to 120,000 base salary
• career progression
• excellent benefits package

• Architect and optimise Snowflake environments (warehouse design, security, cost control)
• Design and develop dbt transformation frameworks with testing, lineage and CI/CD
• Build production-grade SQL and Python data pipelines across multi-source data
• Model scalable data structures for clients, transactions, alerts, risk and investigations
• Establish data quality, lineage, monitoring and governance controls
• Provide technical leadership, set engineering standards and mentor engineers
• Integrate data from AML, KYC, screening, CRM and other systems
• Develop datasets to enable future machine learning, anomaly detection and automation

• Hands-on Snowflake engineering experience (architecture, performance, security, cost control)
• Advanced dbt expertise with production transformation frameworks
• Strong SQL for complex transformations and scalable modelling
• Strong Python for pipelines, automation and integrations
• Experience delivering modern cloud data platforms in complex environments
• Solid Git, CI/CD, automated testing, observability and production support
• Experience leading engineers and owning architecture and delivery
• Experience with sensitive, governed data in financial services or regulated contexts

• leadership and mentoring
• cross-functional collaboration
• strong communicator
• Snowflake
• dbt
• SQL