Staff Software Engineer, Data Infrastructure

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. 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. The Data Foundations team at Patreon builds the pipelines, models, and infrastructure that power both customer-facing and internal data products. 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.

Responsibilities

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 platforms that let engineers, data scientists, and analysts safely discover data, define contracts, and create and operate pipelines with minimal friction; Partner with the broader Infrastructure, Platform, and product engineering to drive architectural decisions across storage, compute, deployment, and orchestration to align the data ecosystem with Patreon’s roadmap; Build the tooling, monitoring, and observability that gives engineers confidence in the data platform's reliability and performance; Mentor other engineers on infrastructure and streaming best practices, and help shape the long-term data infrastructure roadmap.

Requirements

8+ years of software engineering experience, including 4+ years focused on data or platform infrastructure; Deep, hands-on experience architecting both batch (Airflow, Dagster, or similar) and stream processing systems at scale (Spark, Flink, Kafka Streams, or similar); Familiarity with data quality, lineage, observability, and governance tooling; Strong programming skills in Python (Java, Scala, or Go a plus) and SQL; Familiarity with cloud infrastructure and broad fluency across data stores: Object storage (S3), RDMS (MySQL, or Postgres, etc.), Key value (DynamoDB), OLAP (Clickhouse, Pinot, or Druid, etc.), search/indexing (Elasticsearch) plus data flow patterns for keeping them in sync with source systems; Excellent collaboration and communication skills; comfortable driving cross-functional infrastructure decisions; Bachelor's degree in Computer Science, Computer Engineering, or a related field, or the equivalent.

Nice to have

Experience with Delta Lake/Iceberg, AWS, or Databricks; Contributed to open-source streaming or infrastructure tooling; Experience supporting ML/AI workflows, training pipelines, or evaluation systems.

Benefits

salary; equity plans; healthcare; flexible time off; company holidays and recharge days; commuter benefits; lifestyle stipends; learning and development stipends; patronage; parental leave; 401k plan with matching.