Data Engineer, Monetization Data Platform
Build and operate scalable monetization data platforms, pipelines, models, and quality systems spanning product, financial, and operational data. The role partners with Product Engineering, Finance, Accounting, Analytics, and GTM teams to deliver reliable, observable data products.
About the job
Responsibilities
- Design, build, and operate large-scale streaming and batch data pipelines for product, financial, and operational data.
- 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 platform capabilities and frameworks that improve developer productivity and enable trusted monetization data products.
- Partner with Product Engineering, Finance, Accounting, Analytics, and GTM teams to define data contracts and instrument monetization features.
- Lead technical design and delivery of complex cross-functional projects using system designs and RFCs.
- Improve observability and operational excellence through monitoring, incident response, root-cause analysis, and remediation.
- Contribute to engineering standards, documentation, and knowledge sharing.
Requirements
- Deep experience building and operating production data platforms, distributed data systems, or high-scale data pipelines.
- Proficiency in large-scale 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 technical and non-technical partners, navigate ambiguity, and deliver scalable technical solutions.
- Strong communication, engineering judgment, and focus on correctness and operational reliability.
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 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.
Compensation
- Salary range: $230,000–$385,000.
Skills
Python, Java, Scala, Data Pipelines, Data Modeling, Data Architecture, Distributed Systems, Data Quality, Observability, Data Lineage, Data Governance, Workflow Orchestration, Streaming Systems, Data Warehousing
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