GenAI Data Engineer: Cloud Pipelines & Data Governance

Nelnet; Atlanta (GA); Hybrid; USD 115,000 - 135,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

HSA/FSA

401K

Student loan repayment

Life insurance

AD&D

EAP

Stock purchase plan

Tuition reimbursement

Wellness program

Job summary

Nelnet is seeking a Data Pipeline Engineer to own the data foundation underpinning GenAI solutions for higher education and SLED clients. You will build and maintain data pipelines on Google Cloud to ingest, transform, and serve client data for GenAI use cases.

The role requires hands-on experience with BigQuery, Dataflow, ELT/ETL, and data governance—including FERPA compliance—while collaborating with GCP/Gemini Enterprise Engineering and other teams in a hybrid, remote-friendly environment.

Qualifications

• Hands-on experience building data pipelines and ELT/ETL for analytics or GenAI on a major cloud data platform.
• Direct experience with BigQuery and Dataflow (or Cloud Composer/Airflow) strongly preferred.
• Experience with data governance and classification tooling for identifying sensitive data.
• Strong SQL and Python for pipeline development.
• Familiarity with FERPA and education/public sector data considerations.

Responsibilities

• Design, build, and maintain data pipelines using BigQuery and Dataflow for GenAI use cases.
• Develop ELT/ETL processes for batch ingestion from SIS and ERP systems into analytics stores.
• Monitor pipeline reliability, performance, and cost; optimize resource usage.
• Define data access controls and governance for education data; surface compliance risks.
• Collaborate with GCP/Gemini Enterprise Engineering and AgentOps teams; document data flows.

Skills

BigQuery

Dataflow

ELT/ETL

Python

SQL

GCP

Dataplex

DLP

FERPA

Data governance

Education

Bachelor’s degree or equivalent

Tools

Airflow

SIS/ERP data

Job description

Nelnet is seeking a Data Pipeline Engineer to own the data foundation underpinning GenAI solutions for higher education and SLED clients. You will build and maintain data pipelines on Google Cloud to ingest, transform, and serve client data for GenAI use cases.

The role requires hands-on experience with BigQuery, Dataflow, ELT/ETL, and data governance—including FERPA compliance—while collaborating with GCP/Gemini Enterprise Engineering and other teams in a hybrid, remote-friendly environment.