[Hiring] IT Software Engineer - Data @Nelnet

Role Description

This role owns the data foundation underpinning Nelnet’s GenAI solutions for higher education and SLED clients. The Data Engineer builds and maintains the data pipelines, classification, and governance framework required to make client data safely and reliably usable by agentic AI solutions built on the Gemini Enterprise Agent Platform.

• Design, build, and maintain data pipelines using BigQuery and Dataflow (or Cloud Composer/Apache Airflow) to ingest, transform, and serve client data for GenAI use cases.
• Build and maintain ELT/ETL processes for batch ingestion of client source system data (SIS, ERP, casework systems) into Google Cloud analytics and RAG data stores.
• Monitor pipeline reliability, performance, and cost, optimizing BigQuery usage and Dataflow jobs as engagements scale.

Data Classification & AI Readiness:

• Classify and tag client data using Dataplex and Cloud Data Loss Prevention (DLP) to identify sensitive and regulated data, such as FERPA-protected student records, prior to AI use.
• Define and enforce data access controls and governance policies appropriate for higher education and SLED data sensitivity.
• Assess and document data readiness for AI use cases, flagging gaps in quality, completeness, or governance to the Forward Deployed Engineer.

Data Architecture & Integration:

• Design data models and schemas that support both current client use cases and reusable, repeatable data patterns across engagements.
• Partner with client technical teams to understand source system constraints and negotiate data access and extraction approaches.
• Maintain technical documentation of data flows, schemas, and classification decisions for internal reuse and audit purposes.

Delivery Execution & Quality:

• Execute against the delivery backlog owned by the Forward Deployed Engineer, providing technical estimates and flagging data-related delivery risks.
• Partner with the GCP/Gemini Enterprise Engineer to ensure data pipelines feed agentic solutions with the structure and freshness required.
• Conduct data quality reviews and testing to maintain reliability standards across the practice.

Cross-Functional Collaboration:

• Partner with the GCP/Gemini Enterprise Engineer on data structure and access needed for agentic solutions and retrieval-augmented generation (RAG) pipelines.
• Partner with the AgentOps Engineer on infrastructure, security, and environment management for data systems.
• Provide technical input to the Forward Deployed Engineer and Engagement Manager on data-related scope, risk, and timeline.

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 (e.g., BigQuery, Snowflake, Redshift, Synapse) — required.
• Direct experience with BigQuery and Dataflow (or Cloud Composer/Apache Airflow) strongly preferred.
• Experience with data governance and classification tooling for identifying and managing sensitive or regulated data (e.g., Google Cloud Dataplex and Cloud DLP, or equivalent tools such as Collibra, Alation, AWS Macie).
• Working knowledge of cloud storage, messaging, and access-control concepts (e.g., Cloud Storage/S3, Pub/Sub/SNS/SQS, IAM).
• Google Cloud certification preferred (Professional Data Engineer).
• Strong SQL skills and experience with Python for pipeline development and data transformation.
• Familiarity with data privacy and compliance considerations relevant to education or public sector data (e.g., FERPA, state privacy law).
• Experience partnering with client or partner technical teams to extract and integrate data from legacy or third-party systems (SIS, ERP, casework systems).
• Ability to work from a scoped backlog and translate technical requirements from the Forward Deployed Engineer into working data pipelines.

Requirements

• Demonstrates strong technical judgment in structuring data for both immediate client use and long-term reuse.
• Identifies data quality, access, and compliance risks proactively before they affect delivery or client trust.
• Communicates technical data considerations clearly to non-technical stakeholders and the Forward Deployed Engineer.
• Builds for reuse, translating one-off client data work into repeatable technical assets.
• Takes ownership of data reliability and quality from ingestion through AI consumption.
• Collaborates effectively with GCP/Gemini Enterprise Engineering and AgentOps counterparts.
• Maintains composure and problem-solving focus when data quality or access blockers threaten delivery timelines.
• Seeks continuous learning given the fast-evolving nature of the Google Cloud data and AI platform.

Benefits

• Medical, dental, vision, HSA and FSA.
• Generous earned time off.
• 401K/student loan repayment.
• Life insurance & AD&D insurance.
• Employee assistance program.
• Employee stock purchase program.
• Tuition reimbursement.
• Performance-based incentive pay.
• Short- and long-term disability.
• Robust wellness program.