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

Affirm; Phoenix (AZ); In loco; USD 140.000 - 190.000; Tempo pieno

Vantaggi offerti da questo lavoro

100% Subsidized Medical Coverage

Dental Insurance

Vision Insurance

Monthly Tech Spending Stipend

Health and Wellness Stipends

Flexible Time Off

Employee Stock Purchase Plan (ESPP)

Descrizione del lavoro

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.

Competenze

• 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.

Mansioni

• 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.

Conoscenze

Backend Development

Python

Kotlin

AWS

MySQL

Kubernetes

Spark

Airflow

Distributed Systems

Data Pipelines

Batch Processing

System Design

Code Review

Technical Leadership

API Design

Scalability

Formazione

Bachelor's degree in Computer Science or related field

Descrizione del lavoro

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.