Vintage Cash Cow

Senior Data Analyst, Revenue

Leeds, England
SQL Snowflake dbt FiveTran Sigma Power BI Tableau Looker Python
Description

Senior Data Analyst (Revenue)

Department: Data

Employment Type: Full Time

Location: Leeds, England, Trimble Offices, Morley

About the team:
At Vintage Cash Cow, data is how we scale impact. Every customer journey, from sending in pre-loved items to getting paid, is informed by the insights we generate, the models we build, and the decisions we enable. 

Our Data team sits at the heart of this transformation, partnering closely with Technology & Product, and the wider business to turn information into action.   We focus on building trusted, scalable data foundations and delivering insight that drives smarter decisions across the organisation.


This is a team where curiosity meets craft: blending analytical thinking, technical excellence, and a strong commercial mindset to deliver insight that feels clear, useful, and future-focused.


About the role:
We’re looking for a data-first, insight-hungry Data Analyst to help us deepen how data drives decisions across Vintage Cash Cow.  

You’ll own revenue analytics across our entire value chain. From acquisition pricing optimisation across diverse product categories to channel performance and sell-through strategy. Your work will directly influence how we price incoming goods, which sales channels we prioritise, and how we maximise margin across our multi-category, multi-channels business model.


You won’t be starting from scratch, you’ll be joining an established, data-savvy team with strong foundations already in place. Our rebuilt modern data platform (FiveTran, Snowflake, dbt, Sigma) gives you everything you need to dive in fast and make an impact from day one.

Key Goals & Objectives


  • Provide clear, accurate insight into revenue, margin, and performance drivers. 
  • Support pricing, forecasting, and growth decisions with high-quality analysis.
  • Improve speed and confidence in commercial decision-making. 
  • Enable a culture of data-led revenue optimisation across the business. 

Key Responsibilities & Skills


Revenue & Commercial Analytics:
  • Own end-to-end revenue reporting and analysis across product categories and sales channels
  • Build predictive models for pricing optimisation, demand forecasting, and sell-through rates
  • Analyse category-level economics to identify margin opportunities and optimize acquisition pricing
  • Evaluate channel performance to inform strategic resource allocation
  • Partner with commercial teams on A/B testing for pricing strategies and channel experiments
  • Monitor and report on key revenue metrics: ASP by category, channel contribution margin, inventory turns, days to sale, etc.


Commercial Partnership 
  • Partner closely with stakeholders across the business to understand revenue goals. 
  • Translate complex analysis into clear commercial recommendations. 
  • Present insights that directly influence pricing, growth strategy, and operational decisions. 


Continuous Improvement
  • Contribute to developing data best practices, standards, and governance.
  • Collaborate with engineers to improve data pipelines and performance.
  • Stay curious, explore new BI tools, AI integrations, and analytical techniques that can enhance how we use data.




________________________________________________________________________________________________________
Essential Skills & Experience:
  • Expert-level SQL skills with experience building complex data models for financial and commercial analysis 
  • Experience with BI tools (Sigma, Power BI, Tableau, Looker, or similar).
  • Solid understanding of modern data platforms (e.g. Snowflake, dbt, FiveTran).
  • Strong communicator who can translate data into business impact.
  • Strong commercial mindset, you care about revenue impact, not just outputs. 
  • Experience collaborating in cross-functional environments.



Nice to have:


  • Experience in e-commerce, marketplace, or re-commerce business models
  • Knowledge of pricing optimisation techniques or dynamic pricing strategies
  • Experience with experimentation frameworks (A/B testing, incrementality testing)
  • Intermediate knowledge of Python for data analysis.
Vintage Cash Cow
Vintage Cash Cow

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