Senior Analytics Engineer, Finance

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