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Senior Backend Software Engineer (Consumer Data Platform)

Affirm

Join Affirm's Growth Platform Engineering team as a Senior Backend Software Engineer. In this high-impact role, you'll design and build scalable backend systems that drive user acquisition, engagement, and lifecycle growth. Collaborate closely with Product, Data Science, and Experience teams to create APIs, event-driven services, and experimentation frameworks. Your work will directly influence customer experiences and Affirm's overall growth trajectory. Enjoy a remote-first work environment, generous time off, and comprehensive health benefits.

Responsibilities

  • Concevoir et construire des systèmes backend évolutifs, des API et des modèles de données qui alimentent les communications, l'expérimentation et la personnalisation.
  • Collaborer avec les chefs de produit, les scientifiques des données et les analystes pour définir et exécuter des stratégies d'acquisition et d'engagement des clients.
  • Établir et maintenir les meilleures pratiques d'ingénierie pour garantir que les services sont sécurisés, observables et performants à grande échelle.
  • Strong understanding of distributed systems, service-oriented architecture, and how architectural choices affect scalability, reliability, and maintainability

Requirements

  • Proven track record of delivering complex backend systems in production environments
  • 6+ years of experience as a Software Engineer with a focus on backend systems

Experience with AWS or other major cloud providers

  • Demonstrated ability to collaborate effectively across Product, Data Science, Analytics, and Design teams
  • Bachelor’s degree in a related field or equivalent practical experience
  • Proficiency in Python, Kotlin, or similar languages (experience with both is a plus)
  • Excellent written and verbal communication skills, with proficiency in asynchronous communication (design docs, technical specs, project plans, etc.)
  • Experience with experimentation platforms (A/B testing frameworks, feature flagging systems)
  • Exposure to large-scale personalization, recommendation, or messaging systems
  • Familiarity with event-driven architectures and stream processing tools (e.g., Kafka, Kinesis)

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