Data Analyst - Finance

About us

Traditional banking has never really given you control over your financial life. Satispay exists to change that: to empower people through finance .

That means making financial services easy and accessible for over 6.5M users. We started with payments, then benefits, investing, cards... and we’re not done. Not even close.

We follow the same logic every time: find a real problem, solve it properly, then look for the next one. The destination? To build the most loved financial platform in the world.

If you own outcomes rather than tasks, stay close to what users need, and refuse to wait for someone else to fix what's broken — you'll find people here who work exactly in the same way. And together, you'll build something worth being proud of.

What you'll be doing As a Data Analyst, you will be a core member of our Growth & Marketing (G&M) team, taking the data and analytics lead on all Finance initiatives, playing a key role in enhancing decision-making by developing analytical models and self-service data assets that drive impactful solutions for financial planning, reporting, and operational steering.

Here's what that looks like in practice:

Build Financial Analytics & Reporting Capabilities - Develop P&L and cash flow analytics, plan vs. actual monitoring models, and financial KPI frameworks that enable Finance to steer the business with accurate, timely data.

Lead Investor Relations Analytics - Serve as the primary analytics and intelligence partner for Satispay's investors including top-tier VC firms, translating business performance into clear, data-driven narratives that maintain and strengthen those relationships.

Partner with Key Stakeholders - Act as the primary data and analytics partner for Finance, while collaborating closely with Marketing, Operations, and Product, bridging the gap between financial data complexity and business decisions and translating technical findings into clear recommendations.

Build High-Impact Visualisation Tools - Define key financial metrics and develop dashboards and reports that communicate financial insights effectively, empowering self-service across Finance and senior leadership.

Drive Business Economics Analytics - Partner with Finance to develop analytical frameworks across monetisation, unit economics, LTV, payback period, cost structure, and revenue drivers, bridging product performance and financial outcomes to support strategic planning.

Enhance Analytics Through AI-Powered Workflows - Design and implement AI-assisted workflows to automate anomaly detection, surface budget deviations, and unlock efficiencies in the analytical processes supporting budgeting and re-forecasting.

Contribute to Our Data Layer Evolution - Contribute to the development of our data mesh layer by designing financial data models and pipelines that integrate into the company’s federated data strategy, ensuring scalable and governed data ownership.

Who we're looking for This role needs someone with a strong analytical mindset who thrives in a collaborative environment, is detail-oriented, and is ready to take real ownership in a dynamic setting.

Relevant Experience - 4+ years in data-related roles spanning Data Analytics, and BI, with at least 2 years of hands-on experience in high-volume data environments.

Financial Data Expertise - Hands-on experience in financial data modelling, with a solid understanding of P&L structures, cash flow analytics, and plan vs. actual monitoring (familiarity with ERP data schemas like SAP and transforming financial data is highly valued).

Technical Proficiency - Strong command of SQL. Experience with Git and notebook-based analytics such as Jupyter is a plus.

Data Modelling & ETL - Proven experience designing data models, building ETL pipelines, ideally in high-volume, high-frequency financial data environments.

AI Fluency - Comfortable using AI tools day-to-day for analytics, automation, and generating ad-hoc analyses, C-level summaries, and business cases efficiently (proficiency with Claude is a strong plus).

Analytical & Problem-Solving Skills - Comfortable with ambiguity, able to break down complex financial problems into focused workstreams, and deliver evidence-based answers with end-to-end ownership.

Stakeholder Management & Communication - Able to independently lead initiatives across Finance and Marketing domains, efficiently translating technical findings into clear, actionable recommendations.

Unit Economics & Monetisation Knowledge - Familiarity with consumer lifecycle metrics (Acquisition, Activation, Retention, Monetisation) and user economics (ARPU, CAC, LTV, Payback Period) from a financial planning lens (Fintech-specific KPIs are a strong plus).

Data Visualisation - Experience with Hex, Looker, or similar tools to build clear and insightful financial data representations.