Backend Engineer - ML Data Pipelines (Remote)

Triwill Group; United States; Remote; USD 140,000 - 170,000; Full time

Benefits offered by this job

Flexible paid time off

Comprehensive benefits package

Job summary

LiveRamp is seeking a software engineer to design and build backend systems and ML data workflows. You will work with BigQuery, GCS, and cloud services to deliver reliable production pipelines and libraries.

The role requires producing observable, scalable solutions and collaborating with cross-functional teams. You will contribute to data processing, interoperability across teams, and incident response while leveraging Python, SQL, Airflow, and cloud-native tooling to support identity

Qualifications

• 3+ years of professional software engineering experience building backend systems, data pipelines, or ML infrastructure in production environments.
• Strong in at least one backend language such as Python.
• Experience with SQL and data processing on warehouse-scale datasets.
• Hands-on experience with cloud-native data tooling (BigQuery, GCS) and monitoring/observability.

Responsibilities

• Design, build, and maintain ML and data workflows using BigQuery, GCS, and related cloud services.
• Develop backend services, pipeline components, and shared libraries for the agentic platform.
• Improve production observability: monitoring, alerting, retries, timeouts, diagnostics.

Skills

Backend development

Python

SQL

Data pipelines

Observability

Cloud experience

Education

Bachelor's degree in CS/Engineering

Tools

Airflow

BigQuery

Google Cloud Storage

CI/CD

Job description

LiveRamp is seeking a software engineer to design and build backend systems and ML data workflows. You will work with BigQuery, GCS, and cloud services to deliver reliable production pipelines and libraries.

The role requires producing observable, scalable solutions and collaborating with cross-functional teams. You will contribute to data processing, interoperability across teams, and incident response while leveraging Python, SQL, Airflow, and cloud-native tooling to support identity