Zilch
Senior Analytics Engineer
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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 big dreams—to make credit accessible to all. Since then, we’ve achieved double unicorn status and onboarded over 5 million customers. With exciting projects on the horizon and ambitious growth plans, we’d love for you to join us.
About the Role
We are looking for a Senior Finance Data Analyst to join our Finance Data team. This technically deep role sits at the intersection of data engineering and finance analytics, ideal for someone who is as comfortable building robust data models and pipelines, understands financial logic, and thrives in cross-functional collaboration.
You’ll leverage advanced SQL skills, strong data modelling instincts, and the ability to create scalable, well-structured data infrastructure that finance teams can rely on. While finance domain knowledge is valuable, your primary strength lies in data—you think in schemas, pipelines, and systems as much as metrics and reports.
If you excel at solving complex data challenges, prioritise data quality and structure, and want to work in a fast-paced environment where your technical contributions directly influence how the business understands its finances, we’d love to hear from you.
Day-to-Day Responsibilities
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Data modelling & pipeline ownership:
- Design, build, and maintain robust data models and transformation pipelines in dbt (or equivalent tooling).
- Ensure finance data is structured, reliable, and scalable across data warehouses.
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Finance analytics:
- Translate complex financial logic into clean, well-documented SQL and data models for reporting and decision-making.
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Data quality & controls:
- Implement and maintain data quality checks, reconciliation logic, and monitoring for critical finance pipelines.
- Proactively identify and resolve issues before they impact downstream systems.
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Metric governance:
- Define and govern core finance KPIs and metrics, ensuring a single source of truth across the business.
- Document definitions, logic, and ownership clearly.
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Cross-functional collaboration:
- Work closely with Finance, Analytics Engineering, and Product teams to embed data requirements into infrastructure.
- Ensure outputs are fit for purpose for all stakeholders.
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Automation & process improvement:
- Identify and automate manual finance data processes to improve reliability, scalability, and reduce operational workload.
What We’re Looking For
Key Requirements
You are SQL-native—complex queries, window functions, and performance tuning are second nature to you.
- Correctness is non-negotiable—you design data structures and processes with accuracy as the priority.
- Curiosity drives you—you want to understand the business impact of data, not just query it, and easily grasp financial concepts.
- Ownership mindset—you don’t wait for direction; instead, you address gaps in pipelines or processes proactively.
- Clarity in communication—you can explain technical concepts to finance stakeholders and financial logic to engineers.
Technical Skills
- Advanced SQL is mandatory—performance tuning, indexing, and knowledge of warehouses like BigQuery, Snowflake, or Redshift.
- Strong experience in data modelling and hands-on work with dbt or equivalent tools.
- Proficiency in building data quality checks, reconciliation logic, and monitoring frameworks.
- 3–5+ years’ experience in data analysis, analytics engineering, or finance data roles, preferably in financial services or fintech.
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Bonus Skills/Experience
- Deep understanding of financial reporting principles.
- Experience with data orchestration tools like Airflow.
- Scripting knowledge in Python and other languages for automation.
- Background in consumer lending, payments, or embedded finance.
- Experience in an Analytics Engineering or hybrid analyst/engineer role.
Benefits
Compensation & Savings
- Pension scheme.
- Death in Service scheme.
- Income Protection.
- Share Options Scheme for permanent employees.
- 5% cashback on in-app purchases.
- £200 WFH setup stipend.
Health & Wellbeing
Comprehensive Private Medical Insurance, including:
- GP consultations (telephone, video, or face-to-face).
- Prescription coverage.
- In-patient, day-patient, and out-patient care.
- Mental health support.
- Optical, dental, and audiological coverage.
- Physiotherapy.
- Advanced cancer coverage.
- Menopause support.
Employee Assistance Programme (EAP):
- Unlimited mental health sessions.
- 24/7 remote GP and physiotherapy.
- 24/7 emotional and practical support helpline.
- Savings on everyday shopping.
- 1:1 personalised well-being consultations.
- Discounts on gym memberships.
Family-Friendly Policies
- Enhanced maternity, paternity, and adoption pay.
- Extended shared parental leave.
Learning & Development
- Support for professional qualifications.
- Membership fees for professional bodies.
- E-learning suite for courses.
- Internal training programmes.
- FCA & regulatory compliance training.
Workplace Perks
- Flexible working: Office Mon/Wed/Thu, remote Tue/Fri.
- Casual dress code.
- Workplace social events.
- Healthy snacks provided.
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