Software Engineer - Data Infrastructure at Affirm

San Francisco, CA, United States

Posted on Mar 17 2015 (over 2 years ago)




At Affirm we believe the financial industry is fundamentally broken. Not only is the core infrastructure built with technology from the 1970s, but there are a dwindling number of people who say "I trust my bank to look out for me". It doesn’t have to be this way, and it’s our mission to fix this problem. We are using technology to re-imagine and re-build core parts of financial infrastructure to enable cheaper, friendlier and more transparent financial products and services that improve lives. We are based in San Francisco; founded by Max Levchin (founding CTO PayPal), Jeff Kaditz (CDO DeNA/ngmoco), and Nathan Gettings (founding CTO of Palantir); and looking for exceptionally talented and passionate people to join us on our mission.

At Affirm we like all data of all shapes and sizes, which is why we built DataTrain; a real-time high-throughput data processing pipeline. DataTrain is a single pipeline that ties our infrastructure together and is responsible for collecting, prioritizing, relaying, sorting, validating and archiving all log events to different parts of our company and infrastructure ranging from other production services to analytics dashboards as well as data warehouses. If you want to build systems that push the boundaries of real-time computing over massive heterogeneous datasets get on the DataTrain!


  • Architect and build DataTrain v2.
  • Manage data security and access controls across the company.
  • Maintain 99.999% uptime of the data pipeline.
  • Build reusable tools and services to manage, manipulate and report on data ranging from developer tools to financial reporting.
  • Integrate new data sources into the data processing pipeline.
  • Improve and scale our data warehouses.
  • Maintain and build ETL processes.


  • Expert knowledge in one of the following languages: Python, C/C++, Java.
  • Previous experience working w/ modern BigData tools.
  • Experience implementing highly available data storage and archiving systems.
  • Strong understanding of operating system internals.


  • Experience managing large scale data warehouse.
  • Experience maintaining PII compliances on large data sets.
  • Knowledge of cutting edge data processing technologies e.g. Storm, Spark, etc...
  • Background in statistical modeling or machine learning.
  • Background in stream processing or online machine learning.


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