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Senior Analytics Engineer
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Analytics Engineer
Location: London
Contract Type: Outside IR35
About the Role
The focus is on delivering reliable, analytics-ready data solutions that support financial reporting, insight generation, and business decision-making across the organization. This role is centered around transforming complex, messy data into clean, scalable models that power reporting, dashboards, and downstream analytics use cases.
The environment is Azure-based, with Microsoft Fabric and broader data warehousing capabilities across the landscape. The role sits between data engineering and business analytics, with strong ownership across modelling, transformation, and reporting enablement.
What You’ll Be Doing
- Design, build, and maintain scalable analytics data models to support FP&A, financial reporting, and business intelligence use cases
- Develop transformation workflows using SQL and modern cloud-based data platforms to create trusted, analytics-ready datasets
- Work closely with finance, investment, and technical stakeholders to understand reporting requirements and translate them into scalable data models
- Take ownership of messy or fragmented datasets and structure them into usable warehouse layers for reporting and analytics
- Build and optimize semantic and reporting layers to support dashboards, self-service analytics, and operational reporting
- Model financial and investment data across areas such as loans, real estate, and broader investment portfolios
- Develop data warehouse solutions across Microsoft Fabric, Synapse, and the wider Azure environment
- Apply best practices across data modelling, documentation, governance, and data quality
- Support the ongoing evolution of the organization’s data platform, helping establish scalable analytics engineering standards
- Use modern transformation tooling such as dbt where appropriate, while applying strong underlying SQL and data modelling principles
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Skills Required
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- Strong experience working with FP&A in an asset management or investment environment
- Excellent SQL skills and significant experience building complex analytical data models
- Strong understanding of data modelling concepts, including dimensional modelling and warehouse design
- Experience taking complex or poorly structured source data and turning it into robust, reusable models for reporting and analytics
- Experience working with finance and FP&A stakeholders and a strong understanding of financial data, reporting, and analysis
- Experience with Azure-based data platforms, with exposure to technologies such as Microsoft Fabric and Synapse
- Exposure to BI and reporting environments, supporting dashboards and business-facing analytics
- Experience within financial services, ideally asset management, alternative investments, private credit, lending, or real estate
- dbt experience is beneficial but not essential. Strong traditional SQL and data modelling experience is the priority
- Experience building or significantly evolving data platforms and analytics capabilities rather than purely maintaining existing reports
- Ability to work closely with both technical and non-technical stakeholders
- Comfortable operating in evolving environments with a mix of greenfield builds and legacy transformation work
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