Software Engineer, Backend; Streaming

Overview

Join to apply for the Staff Software Engineer, Backend (Streaming) role at Affirm
.

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 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.

• 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.

• 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 queuing.
• 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 framework like Spark, Samza, Flink, Beam etc.
• Hands-on experience with Kafka Connect and Kafka Schema Registry components, understanding their underlying functionality and implementation.
• Solid programming skills in Python, Java or Kotlin.
• Experience with Apache Iceberg table format, CDC tools is a strong plus.
• Knowledge of Relational and No
  
  SQL 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

Pay Grade: P

Equity Grade: 7

Base pay is part of a total compensation package that may include monthly stipends for health, wellness and tech spending, and benefits (including 100% subsidized medical coverage, dental and vision for you and your dependents). CAN base pay range per year: $178,000 - $228,000.

Affirm is remote-first. Some roles may be office-based depending on job responsibilities. Benefits include health care coverage for you and dependents, Flexible Spending Wallets, time off, and ESPP.

Affirm is proud to be an inclusive employer and provides reasonable accommodations during the hiring process where needed.

[For U.S. positions that could be performed in Los Angeles or San Francisco] Pursuant to local fair chance laws, Affirm will consider qualified applicants with arrest and conviction records.

By clicking "Submit Application," you acknowledge that you have read Affirm's Global Candidate Privacy Notice and consent to the collection, processing and storage of your personal information as described therein.