GenAI Data Engineer (Remote) - BigQuery/Dataflow

Nelnet; Trenton (NJ); Hybrid; USD 115,000 - 135,000; Full time

Benefits offered by this job

Hybrid work model

Benefits package

Wellness program

Job summary

Nelnet is seeking a Data Pipeline Engineer to design, build, and maintain data pipelines on Google Cloud for GenAI solutions. You will work with BigQuery, Dataflow, and ELT/ETL processes to ingest, transform, and serve client data with governance and security controls.

The role emphasizes data readiness for AI use cases, data classification, and collaboration with GCP/Gemini teams. A hybrid work model is offered, with a focus on data privacy and FERPA compliance.

Qualifications

• Bachelor’s degree in related field or equivalent work experience.
• Hands-on experience building data pipelines and ELT/ETL for analytics/GenAI on a major cloud data platform (e.g., BigQuery, Dataflow); Strong preference for Google Cloud.
• Experience with data governance and classification tooling (Dataplex, DLP); Google tools preferred.
• Strong SQL and Python for pipeline development and data transformation.
• Knowledge of FERPA and education data privacy.

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 Google Cloud analytics and RAG data stores.
• Monitor pipeline reliability, performance, and cost, optimizing BigQuery and Dataflow.

Skills

BigQuery

Dataflow

Python

SQL

ELT/ETL

Airflow

GCP

Data governance

FERPA

Data modeling

Education

Bachelor’s degree

Tools

Dataplex

DLP

Cloud Composer

Job description

Nelnet is seeking a Data Pipeline Engineer to design, build, and maintain data pipelines on Google Cloud for GenAI solutions. You will work with BigQuery, Dataflow, and ELT/ETL processes to ingest, transform, and serve client data with governance and security controls.

The role emphasizes data readiness for AI use cases, data classification, and collaboration with GCP/Gemini teams. A hybrid work model is offered, with a focus on data privacy and FERPA compliance.