FP&A Data Analyst

вчера

ВеликобританияMiddleHybrid

pythondbt

FP&A Data Analyst responsible for building and maintaining finance data models to support management and investor reporting.

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.

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.
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, management accounts and core finance concepts (accruals, revenue recognition, unit economics)
A quantitative background, through education or experience
Strong attention to detail and a quality-first mindset, while still able to work to tight deadlines
Clear communication: you can explain a variance to a CFO and a data model to an engineer
Initiative to automate repetitive work and improve how things are done

Experience with regulatory or external reporting
Exposure to reconciliations, treasury or general ledger data
Experience with BI tools (Metabase, Looker, Power BI) and orchestration tools (Airflow or similar)
Experience maintaining production code: code review, testing, CI/CD
Spanish or Portuguese proficiency