Affirm is reinventing credit to make it more honest and friendly, giving consumers the flexibility to buy now and pay later without any hidden fees or compounding interest.
Affirm is reinventing credit to make it more honest and friendly, giving consumers the flexibility to buy now and pay later without any hidden fees or compounding interest.
The Streaming team at Affirm forms the backbone of several online and offline workloads at Affirm and drives the strategy for event driven architecture, stream processing, replication, data exploration, discovery and validation. We leverage existing open source technologies like Kafka, Flink, Spark and also build our own as needed to design and build real-time data processing pipelines that handle massive volumes of data across our distributed systems.
As a member of our team you would spend time identifying and executing on new use cases of streaming data infrastructure and frameworks , designing and scaling our existing infrastructure and working closely with other teams to promote the optimal use of data at the company. This role requires deep expertise in stream processing technologies and a passion for building scalable, fault-tolerant data infrastructure.
Key Responsibilities
Design and build data infrastructure systems, services and tools to handle new Affirm products and business requirements that securely scale over millions of users and their transactions.
Build and optimize high-throughput, low-latency data pipelines for critical business applications
Build frameworks and services which will be used by other engineering teams at Affirm to manage billions of dollars in loans and power customer experiences.
Help support the Streaming team that forms the backbone for several online and offline workloads at affirm.
Improve the reliability and efficiency of the Data Platform at scale and high availability.
Collaborate with other teams at Affirm, including ML and Analytics, to deliver streaming solutions based on various use-cases and best practices
Monitor, troubleshoot, and maintain production streaming systems, ensuring high availability and reliability of data systems
What We Look For:
8+ years of industry experience in building large scale production systems.
Strong hands on experience with Apache Kafka or similar streaming solutions for large-scale event streaming and message queueing
Experience building and operating robust and highly available infrastructure.
Experience working with data platforms like Snowflake, Glue or Databricks is a plus
Experience with Confluent Platform (Schema Registry, Tableflow) is a strong plus.
Expertise with at least one stream processing frameworks like Spark, Samza, Flink, Beam etc.
Hands-on experience with Kafka Connect, and Kafka Schema Registry components, understanding its underlying functionality and implementation
Solid programming skills in Python, Java or Kotlin.
Experience with Apache Iceberg table format, CDC (Change Data Capture) tools is a strong plus
Knowledge of Relational and NoSQL databases is a plus.
Experience leading technical projects and mentoring junior engineers.
Exceptionally collaborative with a history of delivering complex technical projects and working closely with stakeholders.
Location - Remote Canada
Affirm is proud to be a remote-first company! The majority of our roles are remote and you can work almost anywhere within the country of employment. Affirmers in proximal roles have the flexibility to work remotely, but will occasionally be required to work out of their assigned Affirm office. A limited number of roles remain office-based due to the nature of their job responsibilities.
We’re extremely proud to offer competitive benefits that are anchored to our core value of people come first. Some key highlights of our benefits package include:
We believe It’s On Us to provide an inclusive interview experience for all, including people with disabilities. We are happy to provide reasonable accommodations to candidates in need of individualized support during the hiring process.
[For U.S. positions that could be performed in Los Angeles or San Francisco] Pursuant to the San Francisco Fair Chance Ordinance and Los Angeles Fair Chance Initiative for Hiring Ordinance, Affirm will consider for employment qualified applicants with arrest and conviction records.
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Affirm is a pay-over-time solution that helps remove price as a barrier for shoppers, enabling merchants to see an 85% increase in average order value and 20% repeat purchase rate. Affirm’s mobile-friendly, omnichannel solution is optimized for e-commerce, in-store transactions, and telesales. Affirm provides the tools merchants need to easily integrate pay-over-time options for shoppers.
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