Data Solutions Manager

Location London - various locations

Salary Competitive salary plus a generous benefits package

Final date to receive applications Tuesday, March 31, 2026

• Partner with senior stakeholders to identify high-impact data and analytics opportunities aligned to firm outcomes (e.g. adoption, AUM growth, adviser productivity, retention)
• Define clear product visions, problem statements and measurable success criteria
• Run demand intake, triage and prioritisation, maintaining a transparent roadmap
• Balance short-term wins with long-term platform coherence

• Translate stakeholder needs into clear, prioritised technical briefs including:

• Data requirements
• Entity definitions
• Metric logic and edge cases
• Acceptance criteria and non-functional considerations

• Produce high-quality delivery artifacts (epics, user stories, validation expectations, release notes)
• Partner with engineers and analysts to shape solution approaches, ensuring feasibility, maintainability and performance
• Manage scope, dependencies and risks to maintain delivery momentum

• Ensure data products are built on sound modelling principles and reusable datasets
• Champion clear metric definitions and semantic consistency across reporting and analytics
• Ensure governance considerations (quality, ownership, access, documentation) are designed into solutions from the outset
• Promote conventions that improve trust and reduce duplication without introducing unnecessary bureaucracy

• Define measurable adoption and impact metrics for each product
• Plan enablement, communication and feedback loops to embed solutions into day-to-day workflows
• Monitor usage, trust and performance, driving continuous iteration
• Establish clear post-launch ownership and lifecycle management

• Be comfortable validating logic, querying data, reviewing metric definitions and testing edge cases
• Provide technical challenge and quality input without becoming a delivery bottleneck
• Support prototyping and rapid experimentation

• Proven experience delivering and iterating data or analytics products end-to-end
• Strong stakeholder management and cross-functional delivery leadership
• Demonstrated ability to prioritise effectively and manage trade-offs
• Working capability in SQL (data exploration, logic validation, metric definition)
• Working capability in Python (analysis, prototyping, automation)
• Strong understanding of data modelling and scalable analytical datasets
• Practical understanding of governance concepts (quality, ownership, access, documentation) and how to embed them into delivery
• Self-starter who creates structure, drives clarity and delivers outcomes

• Experience with analytics engineering patterns and tooling
• Experience building or guiding lightweight front-end/internal apps (e.g., Streamlit, Power Apps, React/Next, or similar) to prototype workflows and accelerate learning
• Exposure to AI/ML delivery lifecycle and operationalisation (data readiness, monitoring, model risk controls)