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Senior Finance Data Analyst

Zilch·UK·Zilch UK·senior
sqldbtdata engineering
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Who we are: Zilch is a payment tech company on a mission to create the most empowering way to pay for anything, anywhere. Combining the best of debit, credit and savings, we give our customers the option to earn instant cashback or spread the cost of pricier purchases, completely interest free and with no late fees. Pretty great, right? We started in 2018 with a small team and a big dream - to make credit accessible to all. Since then, we've achieved double unicorn status and taken on more than 5 million customers. There are some exciting projects coming up and we’ve got big growth plans. Want to join us? About the role. We are looking for a Senior Finance Data Analyst to join our Finance Data team. This is a technically deep role that sits at the boundary of data engineering and finance analytics -ideal for someone who is as comfortable building robust data models and pipelines, understands financial logic and is happy to work with finance stakeholders. You’ll bring advanced SQL skills, strong data modelling instincts, and the ability to build scalable, well-structured data infrastructure that finance teams can rely on. Finance domain knowledge is important, but your primary strength is data - you think in schemas, pipelines, and systems as much as in metrics and reports. If you thrive on solving complex data problems, care deeply about data quality and structure, and want to work in a fast-paced team where your technical contributions directly shape how the business understands its finances - we’d love to hear from you. Day to day responsibilities. - Data modelling & pipeline ownership: Design, build, and maintain robust data models and transformation pipelines in dbt or equivalent tooling, ensuring finance data is structured, reliable, and scalable across the warehouse. - Finance analytics: Translate complex financial logic into clean, well-documented SQL and data models that finance teams can rely on for reporting and decision-making. - Data quality & controls:

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