Senior Analytics Engineer, Finance
We’re looking for a Senior Analytics Engineer to help shape how data is modeled and governed at Airalo, transforming first- and third-party data into clean, trusted, well-documented datasets that power decisions across product, marketing, finance, and commercial teams, serving 30+ million users and growing. This role carries particular weight in our finance and revenue domain: you’ll steward the models finance relies on directly, including order-to-revenue flows and reconciliation against third-party systems such as our ERP, where precision and auditability matter as much as scalability.
Our analytics engineering function is still maturing, so you’ll have real ownership in establishing standards, defining our semantic layer, and shaping how data is structured as we scale globally, working closely with the rest of the data team to build a production-grade analytics platform on LightDash and beyond.
Design, implement, and maintain data models using dbt within our cloud data warehouse, ensuring performance, cost efficiency, and alignment with business logic
Build and maintain finance and revenue data models, including order-to-revenue flows, recognition logic, and reconciliation against source-of-truth financial systems, that finance and commercial teams can rely on for reporting and forecasting
Own the order-to-revenue pipeline: ensuring every order correctly and traceably resolves into recognized revenue, with clear handling of refunds, adjustments, currency conversion, and edge cases
Collaborate with other analytics engineers and data engineers to build and scale ELT workflows that ensure data freshness and reliability for mission-critical reporting
Partner with Finance and the ERP systems integrator to validate that data models and definitions carry over correctly from legacy systems into the new ERP/EPM platform
Implement robust testing, documentation, and monitoring practices, acting as a steward of data quality and governance across the platform, with particularly high attention to detail in domains where small errors compound (e.g., revenue, finance)
Collaborate cross-functionally to translate complex business questions into scalable, production-ready data artifacts
Partner with the data analysts and domain leadership to drive the rollout and adoption of self-service analytics, ensuring business users can trust and independently explore the data models you build
Contribute to the evolution of our modern data stack, bringing curiosity and pragmatic judgment to new tools and approaches
Bachelor's/Master's degree in a quantitative field (statistics, economics, mathematics, computer science, or equivalent work experience)
Hands-on experience building finance and/or revenue data models, ideally including order-to-revenue or billing-to-revenue pipelines, revenue recognition logic, or financial reconciliation (ERP, billing platforms or similar)
5+ years in analytics engineering, data engineering, or analytics roles with significant modeling responsibilities
Strong SQL and data modeling skills, with demonstrated experience designing robust, scalable dimensional models
Exceptional attention to detail, especially when working with numbers that feed financial reporting, reconciliation, or external disclosure
Significant hands-on experience with dbt (Core or Cloud) for managing transformation logic, testing, and documentation
Familiarity with cloud data platforms (BigQuery) and data orchestration tools (Airflow, Dagster, or similar)
Experience working with modern BI platforms and semantic layers-LightDash experience is a strong plus
Track record of partnering with analysts and business stakeholders to translate requirements into well-structured data products
Strong communication skills, with the ability to explain complex data concepts to diverse audiences
Proactive self-starter who thrives on solving ambiguous problems and takes ownership from concept to production
Experience in marketplace, telecom, or travel/mobility businesses
Background in B2C product companies with high-volume event data
Experience building analytics engineering capabilities in low-maturity data environments
Previous experience at a scale-up that went through hypergrowth
Experience defining and governing company-wide KPIs and metric frameworks
Experience working alongside or within a finance function (e.g., supporting FP&A, revenue accounting, or audit processes) on data accuracy and traceability
Why People Join Us
🇪🇸 Why people join us in Spain
We started Airalo to make staying connected effortless, wherever you are in the world. Today, millions of travelers rely on our eSIMs, and many of the people building the product were customers first.
Our team is united by a shared belief that great work happens when people are trusted to own what they do. As Airalo continues to grow, so do the opportunities to learn, take on new challenges, and make a real impact.
For many of our teammates in Spain, it's the combination of stability, flexibility, and genuine work-life balance that makes Airalo feel like home.
🇬🇧 Why people join us in the UK
We started Airalo to make staying connected effortless, wherever you are in the world. Today, millions of travelers rely on our eSIMs, and many of the people building the product first discovered us as customers.
Our team spans 60+ countries, but what people often notice quickly is how work actually feels here. There's trust to own what you do, space to focus without constant layers of process, and a clear sense of what you're responsible for from day one.
As Airalo continues to grow, people tend to stay for a mix of things: the chance to work on a product used globally, the autonomy to shape how they work, and the opportunity to keep taking on new challenges without getting stuck in one lane.
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Company: Airalo
Remote-First Company