Staff Software Engineer (Data Infrastructure)

• 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
• 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
• 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

Benefits

• Health Coverage: Medical, dental, and vision plans are available to our US employees and their dependents. Our plans have a nationwide network and we also cover a primary care concierge membership.
• Balance & Wellness: We offer a generous Flexible Time Off policy, in addition to days throughout the year where everyone takes the same day off to recharge our batteries. Employees and their dependents also have access to therapy, coaching, and Employee Assistance Programs services.
• Family Planning: We provide 20 weeks of paid parental leave, fertility, adoption, and surrogacy benefits, as well as an annual stipend for new additions to your families (including pets!).
• Lifestyle & Learning: You’ll have stipends to fund your personal lifestyle and to support your favorite creators on Patreon, as well as an annual stipend for learning and development.
• Hybrid Work: Our offices are in San Francisco, New York, and Porto. Plus, we have more teammates working remotely around the world.
• Financial Support: We offer employer matching for our retirement plans and Health Savings Account (HSA), as well as access to 1:1 financial guidance with a Certified Financial Planner.

Preferred experience

• Bachelor’s degree in Computer Science, Computer Engineering, or a related field, or the equivalent
• 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
• Familiarity with data quality, lineage, observability, and governance tooling
• Excellent collaboration and communication skills; comfortable driving cross-functional infrastructure decisions
• 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)
• Strong programming skills in Python (Java, Scala, or Go a plus) and SQL
• 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