Data Engineer - Cloud-Native Fraud Data Pipelines

Q2; Austin (TX); Hybrid; USD 110,000 - 160,000; Full time

Benefits offered by this job

Hybrid work

Flexible time off

Career mentoring

Health insurance & parental leave

Volunteer programs

“You Earned It” recognition

Job summary

Q2 in Austin, TX is seeking a software engineer for the Risk & Fraud team to design, implement, test, and operate cloud-native, data-driven services across the Fraud Intelligence Platform. You will work with engineers across the stack to deliver reliable software where accuracy matters.

You will contribute to data movement, pipelines, and storage, using Python, SQL, Airflow, Kafka, Snowflake, and Kubernetes, while growing in a collaborative, hybrid environment with strong mentorship.

Qualifications

• Bachelors in Computer Science, Information Systems or related field; 2+ years of related work experience, or an advanced degree.
• Experience with data transformations, orchestration, and pipelines.
• Proficiency in SQL and NoSQL databases, data warehouses, distributed storage and compute.
• Understanding of software engineering, distributed design and data-centric architectures.
• Experience with data tools: Airflow, dbt, Kafka; Snowflake for data warehousing.
• Proficient in Python, C#, Golang, Bash, SQL; familiarity with CI/CD and IaC.
• Containerization with Kubernetes and Docker; familiarity with cloud platforms.

Responsibilities

• Design, implement, test, and operate cloud-native, data-driven services on the Fraud Intelligence Platform.
• Collaborate with engineers to build reliable software where quality and correctness matter.
• Contribute to data movement, pipelines and data storage across systems.

Skills

Python

SQL

C#

Golang

Bash

Airflow

Kafka

Snowflake

Kubernetes

Docker

PySpark

SageMaker

GitLab

Terraform

Education

Bachelor’s degree in CS/IS

Advanced degree

Tools

GitLab

Azure DevOps

Terraform

Argo CD

dbt

Airflow

Kafka

Snowflake

Job description

Q2 in Austin, TX is seeking a software engineer for the Risk & Fraud team to design, implement, test, and operate cloud-native, data-driven services across the Fraud Intelligence Platform. You will work with engineers across the stack to deliver reliable software where accuracy matters.

You will contribute to data movement, pipelines, and storage, using Python, SQL, Airflow, Kafka, Snowflake, and Kubernetes, while growing in a collaborative, hybrid environment with strong mentorship.