Remote Data Engineer for GenAI Data Pipelines

Nelnet; Town of Boscobel (WI); Hybrid; USD 115,000 - 135,000; Full time

Benefits offered by this job

Medical, dental, vision

HSA and FSA

401(k) plan

Student loan repayment

Life insurance

AD&D insurance

Employee assistance program

Stock purchase plan

Tuition reimbursement

Wellness program

Job summary

Nelnet is seeking a Data Pipeline Engineer to design, build, and maintain data pipelines on Google Cloud for GenAI use cases across higher education and public sector clients.

The role emphasizes data governance, sensitive data handling, and collaboration with GCP/Gemini teams to ensure compliant access and AI readiness, with a hybrid work model combining remote and in-office presence.

Qualifications

• Hands-on experience building data pipelines and ELT/ETL processes for analytics or GenAI use cases.
• Experience with data governance and classification tooling (Dataplex and DLP) for identifying sensitive or regulated data.
• Strong SQL skills and Python for pipeline development and data transformation.
• Experience partnering with client or partner technical teams to extract and integrate data from legacy or third-party systems.
• Knowledge of cloud storage, messaging, and access-control concepts in Google Cloud.

Responsibilities

• Design, build, and maintain data pipelines using BigQuery and Dataflow for GenAI use cases.
• Build and maintain ELT/ETL processes for batch ingestion into analytics data stores.
• Monitor pipeline reliability, performance, and cost, optimizing BigQuery usage and Dataflow jobs.

Skills

BigQuery

Dataflow

SQL

Python

Data governance

Collaboration

Problem solving

Education

Bachelor’s degree or equivalent

Tools

Cloud Composer

Dataplex

DLP

IAM

BigQuery

Airflow

GCP

Job description

Nelnet is seeking a Data Pipeline Engineer to design, build, and maintain data pipelines on Google Cloud for GenAI use cases across higher education and public sector clients.

The role emphasizes data governance, sensitive data handling, and collaboration with GCP/Gemini teams to ensure compliant access and AI readiness, with a hybrid work model combining remote and in-office presence.