At a Glance
- Tasks: Lead the design and delivery of a trusted financial crime data layer.
- Company: Join Rathbones, a leader in financial services with a focus on innovation.
- Benefits: Enjoy competitive salary, flexible working, and opportunities for professional growth.
- Other info: Be part of a dynamic team driving continuous improvement and innovation.
- Why this job: Make a real impact in financial crime prevention using cutting-edge data technologies.
- Qualifications: Experience in data engineering, SQL, Python, and knowledge of financial crime.
The predicted salary is between 75600 - 92400 £ per year.
Role Title: Financial Crime Data Lead
Division: Digital & Functions Technology
Location: Glasgow/Liverpool/London
Contract: Perm
About the Role
The Financial Crime Data Lead is a senior data leadership role with accountability for shaping, building and continuously improving the data foundations that underpin Rathbones’ financial crime capability.
The role is central to creating a trusted financial crime data layer that integrates transaction monitoring, client screening, onboarding, client risk, mandate and CRM data into a single usable foundation for workflow, MI, controls, analytics and future automation.
The role will suit an experienced data leader who can combine SQL, Python, Snowflake, data engineering, AI enablement, data governance and financial crime knowledge to reduce operational risk, improve decisioning and enable a single view of financial crime activity across clients and entities.
What you’ll be responsible for
- Own the design and delivery of the financial crime data layer, bringing together relevant data from ComplyAdvantage, OCS, Salesforce, onboarding, mandate and enterprise data sources.
- Define the canonical financial crime data model covering clients, entities, relationships, alerts, screening outcomes, transactions, risk ratings, cases, decisions, source evidence and audit events.
- Lead data engineering across ingestion, transformation, matching, validation, lineage, quality monitoring and controlled publication into downstream workflow, MI, UX and analytics layers.
- Establish SQL and Python engineering standards for reusable pipelines, data testing, reconciliation, automation, exception handling and maintainable production-grade data products.
- Own Snowflake design patterns for financial crime data, including schemas, role-based access, data sharing, performance optimisation, data lifecycle management and secure analytical consumption.
- Develop operational MI and data products that provide clear visibility of alert volumes, case status, backlog, outcomes, control performance and emerging risk indicators.
- Create the foundations for future AI and automation use cases, including explainable alert optimisation, investigation summaries, anomaly detection, adverse media triage and proactive risk insights.
- Partner with Architecture, Financial Crime SMEs, Risk, Compliance, Operations, Salesforce teams and data platform teams to ensure the data layer supports end-to-end business journeys.
- Define data ownership, stewardship and governance arrangements for financial crime data, including controls over sensitive data, retention, access, usage and auditability.
- Build and lead a focused financial crime data engineering capability, fostering strong engineering discipline, documentation, ownership, code quality and continuous improvement.
About you
If you meet some of these criteria and are excited about the role, we encourage you to apply
- Significant experience leading data engineering, data platform or data product delivery in complex, regulated financial services environments.
- Strong hands-on SQL capability, with experience designing performant queries, reusable data models, analytical marts, reconciliation logic, data quality checks and production-grade transformations.
- Strong Python capability for data engineering and automation, including pandas or PySpark-style transformations, API integration, data validation, orchestration support, testing and reusable code patterns.
- Strong experience with Snowflake or equivalent modern cloud data platforms, including warehouse design, schema modelling, performance tuning, secure data sharing, role-based access and cost-conscious usage.
- Experience integrating data from CRM, workflow, risk, compliance, screening, monitoring and third-party vendor platforms using APIs, files, batch and event-based patterns.
- Good understanding of financial crime data domains, including clients, beneficial owners, transactions, screening results, sanctions/adverse media matches, risk ratings, alerts and case outcomes.
- Practical appreciation of the data challenges that drive false positives, manual remediation, duplicate records, inconsistent workflows and weak auditability.
- Strong understanding of data privacy, information security, regulatory traceability and access controls in sensitive financial crime use cases.
- Strong communication skills, able to translate complex data issues into decisions, priorities and pragmatic delivery plans.
- Proven ability to build capability, set standards and lead teams with pace, ownership, quality and continuous improvement.
- Technical Skills & Engineering Requirements
- Advanced SQL engineering skills, including dimensional and Data Vault-style modelling awareness, query optimisation, window functions, data reconciliation, exception reporting and automated data quality checks.
- Advanced Python skills for data pipelines, API integration, automation and analytical prototyping, with good use of version control, packaging, testing, logging and secure coding practices.
- Strong Snowflake engineering knowledge, including warehouses, databases, schemas, streams, tasks, stages, secure views, masking policies, role-based access, clustering considerations and performance/cost monitoring.
- Experience with orchestration and pipeline tooling such as Azure Data Factory, dbt, Airflow, Dagster or similar, with the ability to define reliable, observable and recoverable data flows.
- Experience with CI/CD and DevOps for data products, including Git branching, pull requests, automated tests, deployment pipelines, environment promotion and rollback controls.
- Knowledge of data quality and observability practices, including source-to-target reconciliation, data contracts, freshness checks, completeness checks, anomaly detection and operational alerting.
- Experience preparing AI-ready datasets, including feature engineering, labelling, training/validation splits, bias checks, explainability inputs and controlled publication of model features.
- Working understanding of machine learning approaches relevant to financial crime, including anomaly detection, entity resolution, network analysis, classification, clustering and alert prioritisation.
- Awareness of GenAI enablement patterns, including retrieval-augmented generation, vector stores, embeddings, secure grounding, prompt evaluation, human review controls and protection of sensitive data.
- Ability to engineer data foundations that support model governance, audit trails, explainability, lineage, monitoring and responsible AI controls in a regulated environment.
Measures of Success
- A trusted financial crime data layer that brings together key monitoring, screening, onboarding, mandate and CRM data sources.
- Clear canonical data model, ownership, lineage and control framework for financial crime data.
- Improved data quality with fewer manual workarounds, reconciliations and operational exceptions.
- Reduced false positives and clearer operational visibility through better data, MI and outcome tracking.
- Reusable SQL, Python and Snowflake engineering patterns that support workflow, UX, reporting, analytics and future automation.
- AI-ready data foundations with appropriate governance, explainability, security and human-in-the-loop controls.
- A high-performing data engineering capability with clear standards, documentation, resilience and delivery discipline.
Financial Crime Data Lead in London employer: Rathbones
Rathbones in Sheffield is an exceptional employer, offering a dynamic and collaborative work culture that prioritises employee growth and development. As a Client Services Executive, you will not only gain invaluable experience in wealth management but also benefit from a supportive team environment that fosters professional advancement and a commitment to high-quality client service.
StudySmarter Expert Advice🤫
We think this is how you could land Financial Crime Data Lead in London
✨Tap into Campus Networks
If you're still in uni, don’t forget to engage with your campus's career services and attend finance-related events. Banks often do presentations and recruitment drives on campus, so put yourself out there and make use of these opportunities to show off your passion for the field.
✨Get Certified
Consider pursuing relevant certifications like the CFA or ACCA while you’re job hunting. They not only beef up your CV but also connect you with professional bodies which can lead to networking opportunities and even job openings in banking and financial services.
✨Connect on Professional Platforms
Join finance-focused groups on platforms like LinkedIn and engage in discussions. This can really help you stand out from the crowd, allowing potential employers to see your knowledge and interest in industry trends. Plus, you might stumble upon job postings shared exclusively within the group.
✨Apply Directly and Be Proactive
Don’t shy away from reaching out directly to firms like Rathbones. Use their websites and apply through them, but also consider following up with a polite email to express your enthusiasm. Being proactive can make a huge difference in getting noticed in the competitive financial services sector.
We think you need these skills to ace Financial Crime Data Lead in London
Some tips for your application 🫡
Show Off Your Numbers!:In the banking and financial services world, quantifiable achievements are key. Make sure your CV highlights your grades in relevant subjects, any financial certifications you hold, and specific projects where you've delivered measurable results. Employers love to see how your skills translate into real-world success.
Tailor Your Cover Letter to the Role:When applying for a full-time position, your cover letter should make a direct connection between your experience and the job description. Don't just state your enthusiasm for finance—dive into how your background in banking or financial analysis sets you apart. Let your passion shine through while being specific about what you can bring to Rathbones.
Include Relevant Financial Software Experience:If you've worked with financial modelling tools or software like Excel, SAP, or specific analytical tools during your studies or internships, bring that up! Highlighting your proficiency can really make your application pop and show you're ready to hit the ground running in a full-time role.
Research and Reflect:Before hitting that 'apply' button on Rathbones's website, do a little digging. Look up their recent projects, values, and culture. Reflecting their ethos in your application can make a huge difference and show you’re genuinely interested in being part of the team!
How to prepare for a job interview at Rathbones
✨Brush Up on Financial Analysis Skills
Make sure you're well-versed in financial concepts and analytical techniques relevant to banking and financial services. Get comfortable with tools like Excel for modelling or financial forecasting, as technical questions in this area are common during interviews with Rathbones.
✨Prepare for Case Studies
Expect to tackle case studies that demonstrate your problem-solving skills in real-world banking scenarios. Familiarise yourself with the types of problems you might face—think risk assessments or investment evaluations—and be ready to articulate your thought process clearly.
✨Show Your Passion for Finance
Since this is a full-time position, employers at Rathbones will be keen to see your genuine interest in finance. Be prepared to discuss recent industry trends or news articles that excite you, showcasing your enthusiasm and engagement with the field.
✨Network with Industry Professionals
Before your interview, reach out to current or former Rathbones employees on platforms like LinkedIn. They'll offer unique insights into the company's culture and the interview process, which can give us a delightful edge in showcasing a good fit for the team.
