IT Softwaree Engineer - Data

Summary

Nelnet is a diversified company providing student loan servicing, professional services, consumer lending, payments processing, renewable energy solutions, and K-12 and higher education services. The Data Software Engineer will build and maintain data pipelines, classification, governance, and integration frameworks on Google Cloud to support GenAI solutions for higher education and SLED clients. The role also focuses on data quality, compliance risk, access controls, and collaboration with technical and delivery teams.

Responsibilities

• 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 — distinct from the live, real-time system access the GCP/Gemini Enterprise Engineer builds for agent tool use
• Monitor pipeline reliability, performance, and cost, optimizing BigQuery usage and Dataflow jobs as engagements scale
• 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
• 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
• 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
• 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

Skills

• 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
• 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) sufficient to ramp quickly on Google Cloud's specific implementations
• 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
• 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
• Proficient in SQL development (complex queries, stored procedures, user defined functions) and performance tuning
• Strong knowledge of the full software development lifecycle with exposure to agile or iterative approaches to delivery preferred
• Proficient in ETL design and development in at least one tool, such as SSIS
• Basic knowledge of C#.net for SSIS scripting
• Understanding of RDBMS principles
• Knowledge of Agile
• Netezza, Postgres SQL experience would be helpful
• Analytical and problem solving skills
• Ability to maintain high level of confidentiality
• Must demonstrate a high level of professionalism, positive attitude, and demeanor
• Accepts responsibility
• Passionate about delivering working software
• Ability to adapt and maintain stress tolerance in a rapidly changing environment
• Ability to work on a distributed team in a virtual environmental and remain motivated and productive
• Strong verbal and written communication skills
• Ability to obtain a security clearance
• Direct experience with BigQuery and Dataflow (or Cloud Composer/Apache Airflow) strongly preferred; candidates with strong GenAI/AI-adjacent data engineering experience on other platforms who can ramp quickly on Google Cloud will be considered
• Direct experience with Google's tools strongly preferred
• Google Cloud certification preferred (Professional Data Engineer), demonstrating hands-on technical fluency; foundational/business-oriented certifications do not satisfy this preference
• Data base design and modeling experience, preferred
• JIRA/TFS experience, preferred

Qualifications

Must Haves

• 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
• 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) sufficient to ramp quickly on Google Cloud's specific implementations
• 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
• 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
• Proficient in SQL development (complex queries, stored procedures, user defined functions) and performance tuning
• Strong knowledge of the full software development lifecycle with exposure to agile or iterative approaches to delivery preferred
• Proficient in ETL design and development in at least one tool, such as SSIS
• Basic knowledge of C#.net for SSIS scripting
• Understanding of RDBMS principles
• Knowledge of Agile
• Netezza, Postgres SQL experience would be helpful
• Analytical and problem solving skills
• Ability to maintain high level of confidentiality
• Must demonstrate a high level of professionalism, positive attitude, and demeanor
• Accepts responsibility
• Passionate about delivering working software
• Ability to adapt and maintain stress tolerance in a rapidly changing environment
• Ability to work on a distributed team in a virtual environmental and remain motivated and productive
• Strong verbal and written communication skills
• Ability to obtain a security clearance

Nice to Haves

• Direct experience with BigQuery and Dataflow (or Cloud Composer/Apache Airflow) strongly preferred; candidates with strong GenAI/AI-adjacent data engineering experience on other platforms who can ramp quickly on Google Cloud will be considered
• direct experience with Google's tools strongly preferred
• Google Cloud certification preferred (Professional Data Engineer), demonstrating hands-on technical fluency; foundational/business-oriented certifications do not satisfy this preference
• Data base design and modeling experience, preferred
• JIRA/TFS experience, preferred

Benefits

• Medical insurance
• Dental insurance
• Vision insurance
• HSA
• 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-term disability
• Long-term disability
• Robust wellness program