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Nooks

Platform Engineer, Revenue Operations

San Francisco (Remote)$200k–$230kfulltimemidAdded 2 days ago

About this role

Nooks seeks a Platform Engineer to own the revenue operations infrastructure backbone, managing a complex ecosystem of CRM systems, data warehouses, and AI-powered automation. This role blends hands-on engineering (data pipelines, production services, agentic workflows) with HubSpot administration and governance, reporting directly to the Director of Revenue Engineering.

What you'll do

  • Design and maintain the revenue data warehouse schema, data models, and ETL pipelines consolidating CRM, product, and billing data
  • Operate and monitor 80+ production services handling account scoring, data syncs, enrichment, and reporting with incident response
  • Build and extend AI agent orchestration infrastructure automating recurring RevOps workflows and GTM processes
  • Architect and maintain integrations between HubSpot, product databases, billing systems, and analytics platforms
  • Administer HubSpot as the primary CRM: object/field architecture, permissions, workflows, governance, and rep-focused optimization
  • Implement CRM data cleanup, deduplication, and governance strategies to maintain data quality at scale

What they're looking for

  • HubSpot Sales Hub administration and configuration
  • SQL and Python for data engineering and automation
  • Data warehouse design and operation (Snowflake, BigQuery, Postgres, etc.)
  • ETL/data pipeline development and orchestration
  • Third-party API integration and error handling
  • AI agent development with tools like Claude Code or Cursor
  • Revenue operations and GTM systems architecture
  • Production monitoring, alerting, and incident response
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Nooks

Nooks builds an AI-driven sales platform that enhances sales agent efficiency and automates revenue-generating tasks for customers. The company is hiring Security Engineers, Software Engineers, Agent Engineers, GTM Engineers, and Solutions Engineers to develop AI features, deploy sales agents, strengthen security, optimize revenue operations, and drive technical sales.

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Likely interview questions

  • Walk us through a production data pipeline you've built—what was the architecture, and how did you handle failures or data inconsistencies?
  • Describe a time you cleaned up CRM data at scale. What governance model did you put in place to prevent future degradation?
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