Experis Scotland
Financial Crime Data Lead
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Financial Crime Data Lead
This is a senior data leadership role focused on building and improving the data foundations that support financial crime operations across a regulated financial services organisation.
The position is responsible for bringing together data from multiple systems into a single, trusted source that can be used for investigations, reporting, analytics, controls, risk management and future automation initiatives.
The successful candidate will combine strong technical data skills with a solid understanding of financial crime processes to help improve decision-making, reduce risk and create better visibility across the organisation.
What you'll be doing
- Leading the design and development of a central financial crime data platform.
- Bringing together data from a range of business systems including customer, risk, compliance and transaction-related sources.
- Creating and maintaining data models that provide a clear view of customers, risk profiles, alerts, investigations and outcomes.
- Driving data engineering best practices across ingestion, transformation, quality monitoring and governance.
- Developing reporting and management information that helps teams understand workloads, trends, control effectiveness and emerging risks.
- Working closely with compliance, risk, technology and operational teams to support end-to-end business processes.
- Establishing strong data ownership, security, auditability and governance standards.
- Building and leading a small, high-performing data engineering capability.
- Supporting future AI and automation opportunities through well-structured and trusted data foundations.
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What they're looking for
- Strong experience leading data engineering, data platform or data product initiatives within regulated environments.
- Advanced SQL and Python skills, with hands-on experience building scalable and reliable data solutions.
- Experience working with modern cloud data platforms such as Snowflake.
- Knowledge of integrating data from multiple internal and external systems using APIs and other integration methods.
- Understanding of financial crime concepts including customer onboarding, risk assessment, transaction monitoring, screening and investigation processes.
- Experience with data governance, security, privacy and regulatory controls.
- Ability to communicate complex technical concepts to business stakeholders in a practical and straightforward way.
- Previous experience developing teams, setting standards and driving continuous improvement.
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Technical environment
The role is heavily focused on SQL, Python and cloud-based data platforms, alongside modern data engineering and DevOps practices. Experience with data orchestration tools, CI/CD pipelines, data quality frameworks and emerging AI technologies would be beneficial.
What success looks like
- A trusted and reliable financial crime data platform used across the business.
- Better data quality and fewer manual interventions.
- Improved reporting and operational visibility.
- Reduced risk through stronger controls and more consistent data.
- Data foundations that support future analytics, automation and AI initiatives.
- A well-established engineering function with clear standards, documentation and governance.
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