Data Analyst

The business is Europe's leading live entertainment platform, owning over 80 festivals including major rock, electronic, and Gen Z-focused events. With F&B playing a huge part in the overall revenue. Working directly alongside the F&B Strategy Lead, the F&B Data Analyst will help build the evidence base that will shape the company's F&B strategy for the next 5 years.

This is not a standard FP&A role. The Data F&B Analyst will work with messy, live event data from multiple systems and help turn it into clear commercial recommendations. What You Will Actually Do Hands-on Revenue Analysis Go beyond top-line revenue.

Analyse product mix, per-outlet performance, and site-level variances. Answer questions like: Why did Bar A outperform Bar B? Was it location, queue times, pricing, product range, or staffing?

Identify the underlying drivers of performance - not just what happened, but why. Working with Large, Messy Datasets Pull sales, volume, and margin data from Square POS across multiple festivals and venues - often inconsistent, incomplete, or differently formatted. Clean, structure, and build insight layers on top of imperfect operational data.

Investigate why "all data is not in one plan" and help build a single source of truth in PowerBI. Comparative Operating Model Analysis Model the financial and operational performance of in-house F&B vs outsourced partners (major contract caterers). Compare good examples vs poor examples within the company's own network.

Benchmark national team performance across different countries - not just totals, but efficiency, throughput, and margin drivers. You will own the data appendix behind that recommendation - every chart, every driver analysis, every unit economics assumption. Must-Haves (Non-Negotiable) Hands-on analysis of revenue streams - you have looked at F&B, product mix, or site-level performance, not just top-line totals.

Evidence of identifying drivers of performance - you can point to a time you figured out why something performed well or poorly, not just reported the number. Experience working with large / messy datasets - you have built insight layers on top of imperfect operational data. Nice to Have (But Not Essential) Experience in live events, festivals, stadiums, or high-volume hospitality.

Familiarity with Square POS or similar EPOS systems. Basic SQL or Python for ad-hoc data pulls. #J-18808-Ljbffr