Senior Analytics Engineer, Finance

What You'll Do:

• 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.

Must Haves:

• 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.

Nice to Have:

• 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.