Data Engineer - Hybrid | Snowflake ELT Pipelines

Nelnet Campus Commerce

Lincoln (NE)

Hybrid

USD 100,000 - 115,000

Full time

9 hours ago
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Benefits offered by this job

Medical benefits
Dental benefits
Vision benefits
401K matching
Tuition reimbursement
Wellness program

Job summary

Nelnet is seeking a Data Engineer to design and automate data infrastructure for analytics and operations. You will build and optimize ELT pipelines, shape Snowflake schemas, and collaborate with Analysts, Product Owners, and Developers to ensure reliable, high-quality data access.

This hybrid role offers a competitive compensation range and a path to impact across our data platforms, with opportunities to work on cross-functional initiatives and data models for scalable solutions.

Qualifications

  • Bachelor's degree or equivalent experience required.
  • Strong SQL and data modeling knowledge required.
  • Experience with Snowflake and ELT pipelines.
  • Proficiency in Python for data movement and automation.

Responsibilities

  • Build, maintain, and optimize data pipelines into/out of data warehouses.
  • Design Snowflake schemas to support analytics workloads.
  • Extract, parse, and validate data from various sources.
  • Implement robust ELT pipelines with scalable ingestion.
  • Ensure data quality and data integrity across systems.
  • Collaborate with Analysts, Product Owners, and Developers.

Skills

SQL
Snowflake features
Data modeling
ELT pipelines
Python
PowerBI
Troubleshooting
Documentation

Education

Bachelor's degree

Tools

dbt
Rivery
PowerBI Dataflows

Job description

Nelnet is seeking a Data Engineer to design and automate data infrastructure for analytics and operations. You will build and optimize ELT pipelines, shape Snowflake schemas, and collaborate with Analysts, Product Owners, and Developers to ensure reliable, high-quality data access.

This hybrid role offers a competitive compensation range and a path to impact across our data platforms, with opportunities to work on cross-functional initiatives and data models for scalable solutions.

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