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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 during a significant change agenda involving data consolidation, process improvement, and quality measurement. The successful candidate will ensure the right data solutions are built, challenging decisions early and enhancing the organization's data capabilities.
Responsibilities
- Define and govern the data mart's modelling approach, including schema selection, grain, conformed dimensions, and semantic layer structure, ensuring future analytical and AI use cases are not precluded.
- Establish data science fundamentals and best practices in modelling, statistical rigour, reproducibility, and documentation for FP&A and data engineering teams.
- 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 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 an honest assessment of the need for sustained data science capability versus tuning existing resources.
- Ensure capability persists beyond the engagement.
Requirements
- Substantial financial services domain experience (fund administration, corporate or fiduciary services, asset servicing, wealth, banking, or insurance), with a strong understanding of business fundamentals.
- Senior practitioner background, typically 10+ years, with significant advisory, lead, or principal experience focused on recommendations.
- Deep expertise in dimensional data modelling, schema design, and semantic layer architecture, with the ability to articulate trade-offs.
- Expert SQL proficiency.
- 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 enterprise-level data quality frameworks and KPIs.
- Evidenced capability-building experience, with a focus on raising the standard of existing teams.
- Executive presence and credibility with technology leadership and finance stakeholders.
- Comfortable operating at enterprise data scale.
Skills
- Data Modelling
- Schema Design
- Semantic Layer Architecture
- SQL
- Python
- Data Quality Frameworks
- KPI Definition
- Microsoft Data Stack (Fabric, Synapse, Power BI)
- Azure AI Foundry
- Financial Services Domain Knowledge
- AI Governance
- Agentic Tooling
Location
- London
Work Type
- Hybrid
- Full-time
Experience Level
- Senior
- 10+ years
Salary/Compensations
- Up to £800 per day
About the Company
- Prestigious, leading international fund and corporate services organization.
- 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.