Data Engineer

Nelnet Business Services (NBS), a division of Nelnet, Inc., provides payment technology and education services to more than 1,200 higher education institutions, nearly 12,000 K-12 schools, and millions of individual students, families, and supporters across the globe. Our culture of service enables us to form long-lasting and trusted partnerships, while our focus on creativity and innovative solutions empowers our customer communities to thrive. The Data Engineer builds and maintains the ingestion pipelines, change-data-capture (CDC) streams, and Bronze-layer infrastructure that bring source-system data into Snowflake reliably, on time, and at the right grain. The Data Engineer ensures data is complete, ordered, and historically preserved — creating the raw material the Analytics Engineer models into governed data products. This is more than an ingestion-only role, and it is built to grow. To start, the Data Engineer owns reliable ingestion and the Bronze layer, and works closely with the Analytics Engineer on the mechanics of getting data into conformed Silver models — including the reconciliation that proves the data ties out end to end. Over time, with Analytics Engineer partnership and Architect support, the Data Engineer develops deeper ownership of conforming work: turning messy, multi-system source data into models that mean the same thing across every source. This is an early hire on a small, capability-based data squad, with a clear growth path, working on the foundational data products of a new data platform. Source-System Ingestion •  Build and maintain CDC and batch pipelines from source systems into the Snowflake Bronze layer using Redpanda, Python, and Dagster. •  Manage source-specific adapters across relational (SQL Server, Oracle), document (MongoDB), API, and file-based sources, and stand up new sources as the platform grows. •  Handle the complexity of consolidating single-tenant source databases into a multi-tenant Snowflake model. •  Implement idempotent load patterns with deduplication so pipelines can re-run safely without producing duplicate or missing records. Bronze Layer Ownership •  Design and maintain raw snapshot tables that preserve source-system state with minimal transformation — the immutable audit trail back to source. •  Implement historical tracking so no data is silently overwritten. •  Handle hard deletes from source systems by tracking deletions in Snowflake rather than losing them. •  Maintain source-schema documentation and change detection — alert when upstream schemas drift unexpectedly. Silver Build — Contribute and Grow (with the Analytics Engineer) •  Build conformed Silver models from the business rules, grain, and conforming logic the Analytics Engineer defines — starting with close guidance and taking on more independence over time. •  Own Bronze-to-Silver reconciliation: row counts and totals tie out, no records lost or double-counted across the transformation. •  Help build and automate the mechanical contract gates — reconciliation tie-out, freshness, and schema validation — as CI/CD checks. •  Apply classification tags at Bronze so columns can promote to Silver, partnering with the data owner and Data Governance on classification decisions. •  Handle incremental logic and performance tuning as models grow in volume, with support as needed. Pipeline Reliability and Observability •  Run and monitor Dagster orchestration — scheduling, retries, failure alerting — and grow into fuller ownership of it, including SLA monitoring, over time. •  Implement data-quality checks at the ingestion boundary (row counts, schema validation, freshness checks). •  Monitor Snowflake concurrent-write limits and tune ingestion patterns to avoid bottlenecks. •  Participate in severity-1 incident response — failed file loads, latency cascades, duplicate transactions, and similar. Platform Collaboration •  Work with Platform Engineering on Docker-based containerization and provisioning of Snowflake databases, schemas, and warehouses. •  Apply required tags (domain, squad, product, layer, environment) to Snowflake objects, Dagster jobs, and streaming topics for cost attribution. •  Participate in the HVR-to-Redpanda CDC migration and validate data integrity during cutover. •  Contribute to shared CI/CD pipeline templates that standardize ingestion and build patterns. Annual compensation for this role is $100,000 depending on experience. This position offers a hybrid work option. Nelnet values flexibility and understands the importance of work-life integration. Our hybrid work environment allows associates living within 30 miles of an office location to work remotely for part of the week, while also fostering collaboration and team connection through in-office presence three days per week. Please note that we are unable to provide visa sponsorship for this position. To be considered, candidates must already be authorized to work in the United States without the need for current or future sponsorship. EDUCATION: Bachelor’s degree in Computer Science, Information Systems, Engineering, Mathematics, or a related field; or an equivalent combination of education and directly related experience. EXPERIENCE: Required: •  Experience building and operating production data pipelines with strong Python and SQL skills. •  Solid working knowledge of relational databases (SQL Server, Oracle, or PostgreSQL). •  Experience implementing data-quality checks at the ingestion boundary — schema-drift detection, row-count validation, freshness monitoring — and reconciling that data ties out end to end. •  General familiarity with data modeling concepts. Will develop in role (mentorship and support provided): •  Conforming data across systems — reconciling differing keys, codes, and grains from multiple sources into a single consistent model. •  Deeper ownership of orchestration (Dagster) — scheduling, retries, failure alerti