As a platform company powering businesses all over the world, Stripe processes payments, runs marketplaces, detects fraud, helps entrepreneurs start an internet business from anywhere in the world.Financial Data team is the single source of truth for all financial data in Stripe. Engineers on Financial Data team build platforms, tools, and products to ensure that Stripe’s financial data is complete, accurate, and timely. It supports data consumers like Accounting, Treasury, Revenue, and Cost. The use cases include reconciliation, financial forecasting, financial data analytics & business intelligence, compliance reporting, and auditing & compliance.
We’re looking for people with a strong background or interest in building successful products or systems; you’re passionate about data, you are comfortable in dealing with lots of moving pieces; and you’re comfortable learning new technologies and systems.
- Build large-scale (petabyte-size) financial data platform/solution/pipelines using Big Data technologies
- Work cross-functionally with many teams: Engineering, Treasury, Finance, Accounting, etc.
- Work on systems critical to Stripe’s future operation, with impact over billions of dollars of payments volume.
- Deeply understand the plumbing of modern payments and financial technology in many countries.
You may be fit for this role if you:
- Have delivered production systems.
- Write high quality code. We work mostly in Ruby, Scala, and Java. However, languages can be learned: we care much more about your general engineering skill than knowledge of a particular language or framework.
- Are interested in understanding Stripe’s complex financial data problems.
- Enjoy working with a diverse group of people with different expertise (for example, ¼ of Stripes work in a country that’s different from the one they grew up in).
Nice to Haves:
- Experience with Spark and Scala.
- Experience with big-data technologies like Presto, Flink, Kafka, Redshift.
- Experience with financial or payments technology, including large-scale reconciliation of datasets, SOX/PCI compliance.