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Data Engineer Sports Analytics Jobs in Nebraska (NOW HIRING)

Data Engineer

Lincoln, NE · Hybrid

$100K/yr

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 ...

Data Engineer

Lincoln, NE · On-site

$100K/yr

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 ...

Data Engineer

Omaha, NE · On-site

$109K - $131K/yr

Cordova is seeking a versatile Senior Data Engineer & Application Developer on behalf of our client ... Analytical Background: A background in mathematical and statistical analysis is highly preferred to ...

Data Engineer

Omaha, NE · On-site

$109K - $131K/yr

The Data Engineer works on internal Company applications, data solutions, and software applications for business development, analysis, and other operations for company personnel, agents, and ...

Data Engineer

Omaha, NE · On-site

$109K - $131K/yr

The Data Engineer works on internal Company applications, data solutions, and software applications for business development, analysis, and other operations for company personnel, agents, and ...

Data Engineer

Omaha, NE · Hybrid

$109K - $131K/yr

The Data Engineer works on internal Company applications, data solutions, and software applications for business development, analysis, and other operations for company personnel, agents, and ...

Data Engineer

Omaha, NE · Hybrid

$109K - $131K/yr

The Data Engineer works on internal Company applications, data solutions, and software applications for business development, analysis, and other operations for company personnel, agents, and ...

Data Engineer 2

Omaha, NE · On-site

$109K - $131K/yr

In the role of Data Engineer 2, we'll count on you to: Build and maintain batch and streaming ... analysis and change management. Integrate transformations into CI/CD workflows (build, test, docs ...

Data Engineer 2

Omaha, NE · On-site

$109K - $131K/yr

... analysis and change management. • Integrate transformations into CI/CD workflows (build, test ... Data Engineering, or equivalent practical experience. • Minimum 3 years of experience in data ...

Lead Data Engineer

Omaha, NE · On-site

$98K - $129K/yr

Work closely with developers, analysts, and business partners to understand data requirements, define transformation logic, and deliver production-ready solutions. * Guide junior engineers by ...

Build and maintain scalable ETL/ELT pipelines supporting enterprise reporting and analytics ... Mentor junior engineers and contribute to a growing data engineering function * Translate complex ...

ETL Data Engineer (W2 Full Time)

Omaha, NE · On-site

$109K - $131K/yr

Partner with developers, analysts, and business stakeholders to deliver solutions that meet operational and strategic needs. Technical Skills 7+ years in data engineering, including ETL tools ...

Build and maintain scalable ETL/ELT pipelines supporting enterprise reporting and analytics ... Mentor junior engineers and contribute to a growing data engineering function * Translate complex ...

Analytics Engineer

Scottsbluff, NE · On-site

$70K - $75K/yr

Bachelor's degree in Data Analytics, Information Systems, Computer Science, or equivalent experience * 2+ years in Business Intelligence, Analytics Engineering, or Process Automation * Experience ...

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Data Engineer Sports Analytics information

How does a data engineer in sports analytics typically collaborate with data scientists and analysts on a project?

As a Data Engineer in Sports Analytics, you’ll regularly work alongside data scientists and analysts to ensure high-quality, reliable data is available for modeling and analysis. Your responsibilities often include building and maintaining data pipelines, transforming raw sports data into usable formats, and optimizing data storage for performance. Effective communication is key, as you’ll need to understand the analytical requirements and adjust pipelines or data sources accordingly. Collaboration often happens through regular meetings, shared documentation, and close feedback loops to align on project goals and data needs.

What is the difference between Data Engineer Sports Analytics vs Data Analyst Sports Analytics?

AspectData Engineer Sports AnalyticsData Analyst Sports Analytics
Primary FocusBuilding and maintaining data pipelines, infrastructure, and databasesAnalyzing data, generating reports, and providing insights
Skills & CertificationsSQL, Python, data warehousing, cloud platformsExcel, SQL, statistical analysis, visualization tools
Work EnvironmentData engineering teams, IT infrastructureBusiness teams, sports analytics departments
Industry UsageSports organizations, tech companies supporting sports dataSports teams, media outlets, betting companies

While Data Engineer Sports Analytics focuses on building and maintaining the data infrastructure necessary for sports data analysis, Data Analyst Sports Analytics concentrates on interpreting that data to generate actionable insights. Both roles are essential in sports analytics but serve different functions within the data ecosystem.

What does a data engineer in sports analytics do?

A Data Engineer in Sports Analytics designs, builds, and maintains the infrastructure and systems that collect, store, and process large volumes of sports-related data. They ensure data pipelines are efficient and reliable so that analysts and data scientists can access accurate information for player performance analysis, game strategy, and business decisions. Their work involves integrating data from various sources, optimizing databases, and implementing best practices in data security and quality, all within the context of the sports industry.

What are the key skills and qualifications needed to thrive as a data engineer in sports analytics?

To thrive as a Data Engineer in Sports Analytics, you need a strong background in computer science, data modeling, and database management, typically supported by a relevant degree and experience with large data sets. Familiarity with tools and technologies such as SQL, Python, Spark, cloud platforms (AWS, Azure), and ETL pipelines is essential, and certifications in these areas can be advantageous. Excellent problem-solving, teamwork, and communication skills help you collaborate with analysts, coaches, and stakeholders to translate data into actionable insights. These competencies ensure the efficient collection, processing, and delivery of high-quality sports data that drive performance analysis and competitive advantage.
What are popular job titles related to Data Engineer Sports Analytics jobs in Nebraska? For Data Engineer Sports Analytics jobs in Nebraska, the most frequently searched job titles are:
Infographic showing various Data Engineer Sports Analytics job openings in Nebraska as of July 2026, with employment types broken down into 89% Full Time, 8% Part Time, 1% Temporary, and 2% Contract. Highlights an 80% Physical, 6% Hybrid, and 14% Remote job distribution.

$100K/yr

Full-time

Medical, Dental, Vision, Life, Retirement

Posted 8 days ago


Job description

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 alerting, SLA monitoring.

The modern streaming / CDC stack - Redpanda for change-data-capture.

Governance-integrated engineering - classification tagging and the promotion gates that depend on it, in partnership with Data Governance.

dbt-based layered modeling (Bronze / Silver / Gold) at production maturity.

Preferred:

Any prior exposure to CDC / streaming platforms (Redpanda, Kafka, or similar).

Experience with a document / NoSQL platform (MongoDB preferred).

Experience with Snowflake (multi-tenant patterns, Snowpipe, tasks, streams).

Containerization and provisioning experience with Docker.

Experience consolidating single-tenant sources into a multi-tenant warehouse.

Exposure to data-governance practices - classification, masking, retention - in a regulated data environment.

Experience with financial, payment, or transaction data, including reconciliation and settlement concepts.

COMPETENCIES - SKILLS/KNOWLEDGE/ABILITIES:

Strong analytical and problem-solving skills, with the discipline to prove data is correct rather than assume it.

Comfort working closely with an Analytics Engineer - taking direction on modeling logic while owning the build and reliability of it.

A genuine interest in growing into conforming and Silver-layer modeling work; coachable and motivated by a defined growth path.

Clear written and verbal communication, including documenting pipelines and surfacing issues early rather than absorbing them silently.

Attention to detail with data quality, historical preservation, and auditability.

Ability to manage competing priorities and participate in incident response with composure.

Collaborative working style across engineering, platform, governance, and product roles.

Our benefits package includes 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, and a robust wellness program. Click here to learn more about our benefits: Benefits & Perks - Nelnet Inc

Nelnet is committed to providing a welcoming and respectful workplace where all associates have the opportunity to succeed. As an Equal Opportunity Employer, we ensure that all qualified applicants are considered for employment. Employment decisions are made without regard to race, color, religion/creed, national origin, gender, sex, marital status, age, disability, use of a guide dog or service animal, sexual orientation, military/veteran status, or any other status protected by federal, state, or local law. We value the unique contributions of every team member and believe that a positive work environment benefits everyone.


Qualified individuals with disabilities who require reasonable accommodations in order to apply or compete for positions at Nelnet may request such accommodations by contacting Corporate Recruiting at 402-486-5725 orcorporaterecruiting@nelnet.net.


Nelnet is a Drug Free and Tobacco Free Workplace.


Use of Artificial Intelligence in Hiring


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