As a Backend Engineer in Data Processing, you help design and build Fraud and Security detection systems leveraging Big data pipelines, Machine Learning and Rust.

 

Responsibilities:

• Design and implementation of micro-services in Rust

• Writing reusable, testable, and efficient code

• Implementation of risk evaluation and anti-fraud systems, or similar scoring and anomaly detection systems

• Pick and design adequate data processing storage and pipelines


• Work with our Fraud/Data Science team or provide the Data Science know-how to support Product requirements

Requirements:

• At least 5 years of experience in software engineering

• Experience with Rust

• Experience writing network services or asynchronous code

• Python, Java or similar work experience

• Working knowledge using Kafka, Pulsar or similar

• Experience using a Linux server environment


• Ability to independently debug problems involving the network and operating system

A strong candidate will also:

• Be familiar with deployment using Docker

• Have previous work experience on Risk scoring or anomaly detection systems

• Have experience with Machine Learning and its ecosystem

• Have experience with other strongly typed programming languages

• Have experience using SQL and distributed data solutions like Spark, Hadoop or Druid

• Be passionate about secure, reliable and fast software