Remote GenAI Data Pipeline Engineer

Nelnet; Columbus (NE); Remote; USD 115,000 - 135,000; Full time

Benefits offered by this job

Hybrid work model

Remote work

Job summary

Nelnet is seeking a Data Pipeline Engineer to design, build, and maintain data pipelines for GenAI use cases on Google Cloud, including BigQuery and Dataflow.

You will classify data with Dataplex and DLP, enforce governance, and partner with GCP/Gemini teams to ensure data readiness for AI solutions while managing scope and risks.

The role requires strong SQL and Python skills, experience with ELT/ETL, and collaboration across delivery, security, and engineering teams in a hybrid work setting.

Qualifications

• Hands-on experience building data pipelines and ELT/ETL for analytics or GenAI on a major cloud platform.

Responsibilities

• Design, build, and maintain data pipelines using BigQuery and Dataflow (or Cloud Composer/Apache Airflow) for GenAI use cases.
• Build and maintain ELT/ETL processes for batch ingestion into Google Cloud analytics and RAG data stores.
• Monitor pipeline reliability, performance, and cost, optimizing BigQuery usage and Dataflow jobs as engagements scale.
• Classify and tag client data using Dataplex and Cloud DLP to identify sensitive data prior to AI use.
• Define and enforce data access controls and governance policies for higher education and SLED data.
• Assess and document data readiness for AI use cases, flagging gaps in quality or governance.

Skills

SQL

Python

Data pipelines

ELT/ETL

BigQuery

Dataflow

Airflow

GCP

Data governance

FERPA awareness

IAM

Education

Bachelor's degree

Tools

BigQuery

Dataflow

Cloud Composer

Dataplex

Cloud DLP

Airflow

Job description

Nelnet is seeking a Data Pipeline Engineer to design, build, and maintain data pipelines for GenAI use cases on Google Cloud, including BigQuery and Dataflow.

You will classify data with Dataplex and DLP, enforce governance, and partner with GCP/Gemini teams to ensure data readiness for AI solutions while managing scope and risks.

The role requires strong SQL and Python skills, experience with ELT/ETL, and collaboration across delivery, security, and engineering teams in a hybrid work setting.