Lead Backend Engineer — Real-Time Data Platforms (AWS/K8s)

Affirm

Phoenix (AZ)

On-site

USD 140,000 - 190,000

Full time

11 days ago
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Benefits offered by this job

100% Subsidized Medical Coverage
Dental Insurance
Vision Insurance
Monthly Tech Spending Stipend
Health and Wellness Stipends
Flexible Time Off
Employee Stock Purchase Plan (ESPP)

Job summary

Affirm is seeking a leading backend engineer to develop and scale data platforms for real-time loan origination and financial reporting. You will own quarterly goals, mentor engineers, and collaborate with product and design teams to solve complex technical problems.

The role requires 4+ years of backend experience in Python or Kotlin, plus distributed systems expertise with AWS, MySQL, and Kubernetes, and proficiency with Spark or Airflow for data pipelines.

Qualifications

  • 4+ years of backend experience with Python or Kotlin.
  • Expertise in distributed systems, AWS, MySQL, and Kubernetes.
  • Proficient in scalable data pipelines using Spark or Airflow.
  • Degree in a related field or equivalent experience.

Responsibilities

  • Lead development and scaling of data platforms for real-time loan origination.
  • Own quarterly goals and mentor engineers.
  • Collaborate with product and design teams to solve complex technical problems.

Skills

Backend Development
Python
Kotlin
AWS
MySQL
Kubernetes
Spark
Airflow
Distributed Systems
Data Pipelines
Batch Processing
System Design
Code Review
Technical Leadership
API Design
Scalability

Education

Bachelor's degree in Computer Science or related field

Job description

Affirm is seeking a leading backend engineer to develop and scale data platforms for real-time loan origination and financial reporting. You will own quarterly goals, mentor engineers, and collaborate with product and design teams to solve complex technical problems.

The role requires 4+ years of backend experience in Python or Kotlin, plus distributed systems expertise with AWS, MySQL, and Kubernetes, and proficiency with Spark or Airflow for data pipelines.

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