Staff Software Engineer, Data Infrastructure

Patreon•San Francisco, CA

5d•$232,000 - $386,000•Hybrid

About The Position

Patreon is seeking a Senior/Staff Software Engineer, Data Infrastructure to support its mission of funding the creative class. 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. 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. The successful candidate will join a small, high-craft team that partners across Product, Data Science, Infrastructure, and the rest of Engineering to ensure the platform is reliable, scalable, and easy for other engineers to build on.

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 Haves

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.

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.