Conduct ad-hoc analyses across the business to answer strategic questions and support decision-making.
Proactively identify trends, anomalies, and emerging patterns in data, surfacing insights that may not be immediately obvious to stakeholders.
Contribute to the development and maintenance of core data models in dbt, ensuring data quality and consistency across the organisation.
Track and analyse performance against budget, providing variance analysis and early warning systems for budget deviations before month-end close.
Conduct deep-dive analyses into revenue streams, profitability, and billing patterns across legal areas and markets.
Support forecasting and scenario modelling for business planning, including pricing changes, market expansion, and other strategic initiatives.
Develop and maintain core data models in dbt for revenue metrics, ensuring consistency and accuracy across teams.
Automate month-end reporting workflows currently handled manually in spreadsheets, while maintaining the flexibility finance teams need.
Establish standardised financial data definitions and documentation to ensure consistency across teams and markets.
Translate Finance team needs into clear data and engineering requirements, owning the relationship between technical implementation and business outcomes.
Support M&A activity including due diligence, integration, and standardisation of financial metrics across entities in the Group.

4+ years in a Data Analytics role, with at least some exposure to finance or revenue analytics, ideally within a high-growth or product-led organisation.
Strong proficiency with SQL for complex data querying and manipulation, combined with advanced spreadsheet skills (Excel/Google Sheets) for financial modelling and ad-hoc analysis.
Solid understanding of revenue metrics and financial concepts: gross vs net revenue, deferred revenue, cost allocation, margin analysis, and multi-currency reporting.
Strong communication skills with the ability to translate complex data findings into clear recommendations for both technical and non-technical audiences.
Proficiency with BI and reporting tools such as Hex, Tableau, Looker, or similar.
Proven ability to thrive in a fast-paced environment where finance reporting needs can shift with business priorities.

Data Analyst

Key skills