Finance Data Analyst

Finance Data Analyst – ALF Retained Search

Hybrid (2 days per week in Manchester)

£45-50k + excellent benefits

PE-Backed | High-Growth | Fin Tech

ALF Recruit are delighted to be retained exclusively by a high-growth, PE-backed, Fin Tech provider who sit at the intersection of financial services, data, and technology. This organisation connects financial intermediaries and lenders with a panel of the UK’s leading Financial Services businesses and continues to scale at pace.

They are now looking to appoint a Finance Data Analyst, a newly created role sitting at the heart of Finance and acting as the bridge between financial insight and data capability. You’ll be responsible for extracting, transforming, and analysing financial and operational data, turning it into high-quality insight that drives smarter, faster decisions across the business.

What you’ll be doing

• Own data extraction and financial reporting pipelines, supporting budgeting, forecasting and value-add MI.
• Analyse large, complex data sets to spot trends, risks and opportunities across key KPIs.
• Translate Finance requirements into structured technical briefs for the Data Engineering team.
• Standardise and automate core dashboards and reporting templates (Power BI or equivalent).
• Deliver high-quality ad-hoc analysis, scenario modelling and commercial deep dives.
• Identify and resolve data quality issues, improving controls and data integrity.
• Promote data literacy across the business through storytelling, visualisation, and training support.

What we’re looking for

• Experience in a data-driven or Finance/FP&A/BI analytical role, ideally in a tech-enabled or PE-backed environment.
• Strong experience building or contributing automated dashboards and scalable reporting tools.
• Excellent communication and stakeholder management, able to turn data into clear narrative.
• SQL skills, with the ability to write and optimise queries.
• Strong BI tool capability (Power BI, Tableau) and understanding of data modelling.
• High-level Excel and data manipulation skills.
• Commercially aware, curious, and comfortable challenging assumptions.
• Solid understanding of financial and operational metrics in a commercial environment.