Staff Software Engineer, Data Infrastructure
Company: Patreon
Location: San Francisco
Salary: $257k - $386k per year
Type: Full-time
Posted: 2026-08-06
About this role
Patreon is a media and community platform where over 300,000 creators give their biggest fans access to exclusive work and experiences. We offer creators a variety of ways to engage with their fans and build a lasting business including: paid memberships, free memberships, community chats, live video, and selling to fans directly with one-time purchases.
Ultimately our goal is simple: fund the creative class. And we're leaders in that space, with:
- $10 billion+ generated by creators since Patreon's inception
- 100 million+ free memberships for fans who may not be ready to pay just yet, and
- 25 million+ paid memberships on Patreon today.
We're continuing to invest heavily in building the best creator platform with the best team in the creator economy and are looking for a Senior/Staff Software Engineer, Data Infrastructure to support our mission.
*This role is remote, with optional in-person attendance in either the New York or San Francisco office.*
About the Team
The Data Foundations team at Patreon builds the pipelines, models, and infrastructure that power both customer-facing and internal data products. The Data Infrastructure function within the team owns the foundational platform — streaming, batch, and data lake infrastructure — that every data pipeline, analytics workload, and ML system at Patreon runs on.
You'll join a small, high-craft team that partners across Product, Data Science, Infrastructure, and the rest of Engineering to make sure the platform underneath all of that work is reliable, scalable, and easy for other engineers to build on.
About the Role
- Architect, build, and operate large scale batch and streaming platforms that directly power Patreon product features, analytics, and experimentation.
- Stand up and scale event-driven and streaming systems (Kafka, Kinesis, PubSub, or similar) for real-time data ingestion, transformation, aggregation, and delivery to different data storage systems.
- Build self-serve data platfo...