Data Engineer, Monetization Data Platform

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.

Responsibilities

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 iterate on monetization products using trusted data; Partner with Product Engineering, Finance, Accounting, Analytics, and GTM teams to define data contracts, instrument new monetization features, and translate product and business requirements into robust technical solutions; Lead the technical design and delivery of complex, cross-functional projects, using clear system designs and RFCs to align partners before implementation and making sound tradeoffs among speed, scalability, reliability, and maintainability; Improve the observability and operational excellence of critical data workflows, including monitoring, incident response, root-cause analysis, and long-term remediation; Command strong sense of engineering excellence, contribute to a design-before-implementation approach with clear documentation, and knowledge sharing across teams to elevate the broader engineering organization

Requirements

Deep experience building and operating production data platforms, distributed data systems, or high-scale data pipelines; Highly proficient in large data pipeline architecture and at least one general-purpose programming language such as Python, Java, or Scala; Strong fundamentals in data modeling, data architecture, distributed systems, and software engineering; Designed systems with rigorous data quality, observability, lineage, governance, privacy, or access-control requirements; Ability to collaborate with cross-functional partners to identify needs, navigate ambiguity, and drive progress from problem definition through delivery; Product-oriented mindset and clear communication with technical and non-technical partners, translating customer and business problems into precise data contracts and scalable system designs; Deep care about correctness and operational reliability while maintaining a practical bias toward delivering value; Strong sense of engineering excellence, clear thinking, sound judgment, and a design-before-implementation approach to create maintainable systems

Nice to have

Experience with monetization, pricing, product usage, billing, ads, payments, revenue, or financial data; Familiarity with financial controls, reconciliation, close processes, or audit requirements; Experience with modern lakehouse or data warehouse technologies, workflow orchestration, streaming systems, and data transformation frameworks; Experience building self-service data platforms, shared frameworks, or developer tooling used by other data and engineering teams; Monetization or finance domain experience is helpful but not required