FP&A Data Analyst

Job description

What we're looking for Do you like knowing exactly why a number moved? As an FP&A Data Analyst at ARQ, you'll own the data foundations behind our revenue, cost and management reporting. You'll sit between Finance and Engineering: building the models that tell us how the business is performing, keeping them accurate every day, and turning them into insight that leadership uses to make decisions. This is a hands-on role for someone who is as comfortable in a dbt project or a Python codebase as in a P&L. You'll work closely with Finance, Treasury and Engineering, and your work will feed management, investor and regulatory reporting directly. What you'll be doing Own the finance data layer: Maintain and extend our dbt repo. That means building and refactoring models, writing tests, and keeping finance data clean, documented and reliable. Revenue and cost models: Build and maintain the models behind revenue, unit economics and operations costs (payment rails, FX, card, banking partners, vendors) across our markets. Management accounts: Support daily and monthly management accounts on both accrual and cash basis. Reconcile them to source systems and explain movements. Budgeting and forecasting: Feed actuals into the budget and forecast, run variance analysis, and help Finance understand what is driving performance. Python services: Help maintain and improve the internal Python services and pipelines that support finance reporting and reconciliation. Data mapping and requirements: Map data sources across our product and payments stack, and document business logic and assumptions so others can trust and reuse your work. Onboard new business: When we launch a new product, partner or market, make sure it flows correctly into financial reporting, controls and processes. Dashboards and reporting: Build and improve dashboards with Finance and Controllership that track key metrics and surface business drivers. Anomalies and controls: Spot breaks, unusual spikes or data quality issues early, find the root cause, and fix it at the source. Data literacy: Help the wider team understand and self-serve finance data. What you'll need 3+ years in a data, analytics or FP&A role, ideally in fintech, banking or payments Strong SQL and solid Python Hands-on experience with dbt (or a similar transformation tool) and version control (Git) A good grasp of financial statements, manageme…