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About the Role
This senior role provides advisory and technical guidance for a foundational data program within a leading international fund and corporate services organization. The focus is on making critical structural decisions for a significant change agenda involving data consolidation, clean data initiatives, and data quality measurement. The successful candidate will ensure the right data solutions are built, challenge structural decisions, and enhance the organization's data capabilities.
Responsibilities
- Define and govern the modelling approach for the client's new data mart, including schema selection, grain, conformed dimensions, and semantic layer structure, ensuring future analytical or AI use cases are not precluded.
- Establish data science fundamentals and best practices across FP&A and data engineering teams, covering modelling discipline, statistical rigour, reproducibility, and documentation standards.
- Review team outputs and provide structured feedback.
- Define data quality dimensions, KPIs, and measurement approaches, advising on instrumentation and reporting.
- Assess the analytical readiness of the current data estate and prioritize remediation and cleansing efforts.
- Deliver structured education and upskilling through working sessions and written standards to ensure lasting capability.
- Advise on data governance implications for downstream AI and agentic tooling, including data segregation, permissible use controls, and auditability.
- Provide a clear assessment of where sustained data science capability is needed versus where existing capability requires tuning.
Requirements
- Substantial financial services domain experience (fund administration, corporate or fiduciary services, asset servicing, wealth, banking, or insurance), with a fundamental understanding of the business.
- Senior practitioner background (typically 10+ years) with significant experience in an advisory, lead, or principal capacity, delivering recommendations.
- Deep expertise in dimensional data modelling, schema design, and semantic layer architecture, with the ability to articulate trade-offs between modelling approaches.
- Expert SQL skills.
- Strong Python skills for analysis and validation.
- Practical experience with the Microsoft data stack (Fabric, Synapse, Power BI semantic models), and ideally Azure AI Foundry.
- Demonstrable experience defining data quality frameworks and KPIs in an enterprise setting.
- Evidenced capability-building experience, with a focus on raising the standard of an existing team.
- Executive presence and credibility with technology leadership and finance stakeholders.
- Comfortable operating at enterprise data scale.
Skills
- Data Science
- Data Modelling
- Schema Design
- Semantic Layer Architecture
- SQL
- Python
- Microsoft Data Stack (Fabric, Synapse, Power BI)
- Azure AI Foundry
- Data Quality Frameworks
- KPI Definition
- Capability Building
- Executive Presence
Location
- London
Work Type
- Hybrid
- Part-time
Experience Level
- Senior
- 10+ years
Salary/Compensations
- Up to £1500 per day
About the Company
- A prestigious, leading international fund and corporate services organisation.
- Midway through a significant change agenda: consolidating a fragmented core administration estate and investing seriously in clean data, consistent data processes, and data quality measurement.