Senior Product Manager, Fivetran

• 4+ years of PM experience delivering developer-facing products (SDKs, APIs, platforms)
• Hands-on experience with Python to do data analysis, integrating with APIs, etc
• Knowledge of container management/orchestration platforms, CI/CD, Terraform, and orchestrators such as Airflow or Dagster
• Hands-on experience leveraging or building AI coding assistants (GitHub Copilot, CodeWhisperer, or custom LLM agents) to accelerate Python development, enforce best practices, and boost code accuracy
• Proven track record of shipping products for technical users that have delivered measurable results
• Proven ability to develop deep customer empathy and articulate customer problems
• Demonstrated experience using data and analytical abilities to solve problems and make decisions
• Excellent written and verbal communication skills

Desirable

• As Senior Product Manager of Fivetran’s SDK portfolio you will own the portfolio that enables customers and partners to build on Fivetran’s data integration platform
• Our Connector SDK is a Python library that lets data engineers create a custom connector to extract data source for any source in minutes
• Our Partner SDK enables Partners to build source and destination connectors and make them available to all Fivetran customers
• You’ll be a product leader that collaborates closely with engineering, marketing, sales, sales/solution engineering, and developer relations to drive customer adoption and functionality of our SDKs
• This is a key company priority and is a critical feature for our most important customers
• Strategy & roadmap – Prioritize features that cut average custom connector development time from hours to minutes and expand functionality and data movement options provided by the SDK offerings
• Cross-functional leadership – Partner with Connector Engineering, Solutions Architects, Analytics, Support, and Marketing to launch and grow SDK features
• Developer experience – Design intuitive code interfaces, keep the docs/code samples in lock-step, and champion first-run success
• AI-assisted developer workflow – Integrate LLM-powered agents and coding copilots into the SDK tool-chain (e.g., CLI “generate connector” wizards, schema-mapping suggestions, automated test scaffolds) to cut time-to-first-run and reduce error rates
• Quality & compatibility – Define upgrade and rollout strategies that ensure un-interrupted operation and high reliability and performance
• Adoption & community metrics – Track revenue, revenue weight usage, and churn metrics for the core API as well as pypi downloads, example use and other community engagement metrics; iterating with DevRel