Data Engineer, Monetization Data Platform

Details

The Monetization Data Platform team builds trusted data and platform foundations that support the development, measurement, and improvement of monetization products. The team works with 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.

The role involves building scalable data products and platform capabilities at the intersection of data engineering, product engineering, platform engineering, Finance, and GTM.

Responsibilities

• Design, build, and operate large streaming and batch data pipelines processing product, financial, and operational data from internal and external systems.
• Develop canonical data models and reusable data products for product usage, pricing, billing, ads, payments, revenue, and general ledger domains.
• Establish guarantees for data accuracy, completeness, freshness, lineage, reconciliation, and auditability.
• Build frameworks and platform capabilities that improve developer productivity and support the launch, measurement, and iteration of monetization products.
• Partner with Product Engineering, Finance, Accounting, Analytics, and GTM teams to define data contracts, instrument monetization features, and translate business requirements into technical solutions.
• Lead the technical design and delivery of complex, cross-functional projects using system designs and RFCs to align stakeholders.
• Make tradeoffs among speed, scalability, reliability, and maintainability.
• Improve observability and operational excellence for critical data workflows, including monitoring, incident response, root-cause analysis, and long-term remediation.
• Contribute to engineering excellence, design-before-implementation practices, documentation, and knowledge sharing.

Requirements

• Deep experience building and operating production data platforms, distributed data systems, or high-scale data pipelines.
• High proficiency 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.
• Experience designing systems with rigorous data quality, observability, lineage, governance, privacy, or access-control requirements.
• Ability to collaborate with cross-functional partners, navigate ambiguity, and drive projects from problem definition through delivery.
• A product-oriented mindset and clear communication skills with technical and non-technical partners.
• Ability to translate customer and business problems into precise data contracts and scalable system designs.
• Strong focus on correctness, operational reliability, engineering excellence, sound judgment, and 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 for data and engineering teams.

Benefits

• Base salary of $230,000–$385,000 per year.
• Equity, performance-related bonuses for eligible employees, and comprehensive benefits.
• Medical, dental, and vision insurance, with employer contributions to Health Savings Accounts.
• Pre-tax accounts for health, dependent care, and commuter expenses.
• 401(k) retirement plan with employer match.
• Paid parental, medical, and caregiver leave.
• Paid time off, company holidays, office closures, and sick or safe time.
• Mental health and wellness support.
• Employer-paid basic life and disability coverage.
• Annual learning and development stipend.
• Daily meals in offices and eligible meal delivery credits.
• Relocation support for eligible employees.