Remote GenAI Data Engineer — Cloud Pipelines & Governance

Nelnet; Springfield (IL); Remote; USD 115,000 - 135,000; Full time

Job summary

Nelnet is hiring a Data Pipeline Engineer to design, build, and maintain data pipelines on Google Cloud for GenAI use cases, ensuring data is clean, classified, and access-controlled for AI-ready use. You will work within the GenAI delivery team, collaborating with GCP/Gemini and Forward Deployed Engineers.

The role requires hands-on experience with BigQuery/Dataflow, ELT/ETL processes, and data governance tooling, with a focus on FERPA-sensitive education data and scalable data architecture.

Qualifications

• Bachelor’s degree in related field or equivalent work experience.
• Hands-on experience building data pipelines and ELT/ETL processes for analytics or GenAI use cases on a major cloud data platform.
• Direct experience with BigQuery and Dataflow (or Cloud Composer/Apache Airflow).
• Experience with data governance and classification tooling (Dataplex, Cloud DLP) and familiarity with FERPA or similar standards.
• Strong SQL and Python for pipeline development and data transformation.

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 and RAG data stores.
• Monitor pipeline reliability, performance, and cost; optimize BigQuery/Dataflow usage.

Skills

SQL development

Python

Data pipelines/ELT

Data governance

Data quality assurance

Education

Bachelor’s degree or equivalent

Tools

BigQuery

Dataflow

Cloud Composer

Airflow

Dataplex

DLP

Job description

Nelnet is hiring a Data Pipeline Engineer to design, build, and maintain data pipelines on Google Cloud for GenAI use cases, ensuring data is clean, classified, and access-controlled for AI-ready use. You will work within the GenAI delivery team, collaborating with GCP/Gemini and Forward Deployed Engineers.

The role requires hands-on experience with BigQuery/Dataflow, ELT/ETL processes, and data governance tooling, with a focus on FERPA-sensitive education data and scalable data architecture.