Senior Analytics Engineer

DW Search; Greater London; On-site; GBP 65,000 - 90,000; Full time

Job summary

We are seeking a data analytics engineer to transform complex, messy data into clean, scalable models powering reporting, dashboards and downstream analytics across an Azure-based data stack (Fabric, Synapse). The role sits between data engineering and business analytics with ownership of modelling, transformation and reporting enablement.

You will design and maintain analytics data models for FP&A and financial reporting, develop transformation workflows, and collaborate with finance

Qualifications

• Strong SQL skills and significant experience building complex analytical data models.
• Solid 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.

Responsibilities

• Design, build and maintain scalable analytics data models to support FP&A, financial reporting and BI use cases.
• Develop transformation workflows using SQL and cloud-based data platforms to create trusted datasets.
• Collaborate with finance and technical stakeholders to translate reporting requirements into scalable data models.
• Structure messy datasets into usable warehouse layers for reporting and analytics.
• Build and optimise semantic and reporting layers to support dashboards and self-service analytics.

Skills

SQL

Data modelling

Dimensional modelling

dbt

Azure Synapse

Tools

Microsoft Fabric

Synapse

dbt

Job description

The focus is on delivering reliable, analytics-ready data solutions that support financial reporting, insight generation and business decision-making across the organisation. This role is centred 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 optimise 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 organisation’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

Skills required

• 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