Workplace
On-site
Employment
Full-Time
Published
Aug 20, 2026
Closes
No date supplied
The role
ABOUT THE TEAM The Monetization Data Platform team builds the trusted data and platform foundations that power how the company develops, measures, and improves monetization products. We bring together product usage, pricing, billing, ads, payments, and financial data to help Product, Engineering, Finance, and GTM teams make better decisions and deliver reliable customer experiences. We work at the intersection of data engineering, product engineering, platform engineering, Finance, and GTM. Our goal is to turn complex monetization and financial data into accurate, explainable, and timely data products while building systems that scale with the growth and complexity of the business. ABOUT THE ROLE We are looking for a Data Engineer to improve and build the next generation of our monetization data platform. You will own high-impact systems end to end, from product instrumentation, source ingestion, and canonical modeling through quality controls, observability, and delivery to downstream consumers. This is a hands-on role for an engineer who enjoys solving ambiguous product and data problems, designing durable architectures, and partnering closely with Product Engineering, Finance, Accounting, and GTM. You will help define technical direction, raise the engineering bar, and turn monetization opportunities into trusted, scalable data products and platform capabilities. IN THIS ROLE, YOU WILL - Design, build, and operate large streaming and batch data pipelines that process product, financial, and operational data from a variety of internal and external systems. - Develop canonical data models and reusable data products for domains such as product usage, pricing, billing, ads, payments, revenue, and the general ledger. - Establish strong guarantees for data accuracy, completeness, freshness, lineage, reconciliation, and auditability. - Build frameworks and platform capabilities that improve developer productivity and make it easier for teams to launch, measure, and iter
Requirements
Department: Applied AI; Team: Applied AI Engineering