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Manager Data Engineering Jobs in Nebraska (NOW HIRING)

HDR

Data Engineer 2

Omaha, NE · On-site

$109K - $131K/yr

Use dependency management patterns to ensure correct build order and reproducible transformations ... A minimum of 3 years of experience in data engineering, data integration, or related roles.

HDR

Data Engineer 2

Omaha, NE · On-site

$109K - $131K/yr

Use dependency management patterns to ensure correct build order and reproducible transformations ... A minimum of 3 years of experience in data engineering, data integration, or related roles.

Snowrelic Inc

ETL Data Engineer (W2 Full Time)

Omaha, NE · On-site

$109K - $131K/yr

Troubleshoot issues, manage code deployments, and provide rotational on-call support to maintain ... Technical Skills 7+ years in data engineering, including ETL tools (Informatica, DataStage, DBT ...

HURRDAT LLC

Data Engineer

Omaha, NE · On-site

$80 - $90/hr

Support warehouse performance and cost management through partitioning, clustering, and query ... Two to four years of experience in data engineering, analytics engineering, or business ...

HURRDAT LLC

Data Engineer

Omaha, NE · On-site

$80K - $90K/yr

Support warehouse performance and cost management through partitioning, clustering, and query ... Two to four years of experience in data engineering, analytics engineering, or business ...

Hurrdat

Data Engineer

Omaha, NE · On-site

$80 - $90/hr

Support warehouse performance and cost management through partitioning, clustering, and query ... Two to four years of experience in data engineering, analytics engineering, or business ...

Kemper

Senior Data Systems Analyst

Omaha, NE · On-site

... Management * Investigate production data incidents and quality issues. * Perform root cause analysis and identify corrective and preventive actions. * Partner with engineering and operational teams ...

Snowrelic Inc

Lead Data Engineer

Omaha, NE · On-site

$98K - $129K/yr

Onsite Job Type: Full-Time Reports To: Sr. Manager of Data Engineering Capstone IT is helping a premier client to hire an experienced Lead Data Engineer to lead the development and optimization of ...

Nelnet, Inc.

Managing Director, Data & AI

Lincoln, NE · On-site

$230 - $250/hr

The Managing Director, Data & AI owns the full data-to-AI value chain, aligning data strategy ... Value Chain Unification - Unify data engineering, governance, and AI/automation into a single ...

Socket.dev

Managing Director, Data & AI

Lincoln, NE · On-site

$190 - $320/hr

The Managing Director, Data & AI owns the full data-to-AI value chain, aligning data strategy ... Value Chain Unification - Unify data engineering, governance, and AI/automation into a single ...

Nelnet, Inc.

Managing Director, Data & AI

Lincoln, NE · On-site

$230K - $250K/yr

The Managing Director, Data & AI owns the full data-to-AI value chain, aligning data strategy ... Value Chain Unification - Unify data engineering, governance, and AI/automation into a single ...

Meta

NE · On-site

$150K/yr

Meta is seeking a Regional Quality Manager to join our Data Center Design, Engineering & Construction Team. Our team's mission is to optimize the delivery of our Data Centers, ensuring they are ...

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Showing results 21-40

All JobsData Engineering JobsManager Data Engineering JobsManager Data Engineering Jobs in Nebraska

Manager Data Engineering information

See Nebraska salary details

$29.6K

$92.6K

$164K

How much do manager data engineering jobs pay per year?

As of Sep 3, 2026, the average yearly pay for manager data engineering in Nebraska is $92,623.00, according to ZipRecruiter salary data. Most workers in this role earn between $62,900.00 and $119,700.00 per year, depending on experience, location, and employer.

What are the roles and responsibilities of a manager data engineering?

A Manager Data Engineering oversees teams that design, build, and maintain data infrastructure and pipelines for organizations. They are responsible for ensuring the efficient flow and storage of data, implementing best practices in data management, and collaborating with stakeholders to meet business data needs. Additionally, they mentor and guide data engineers, manage project timelines, and ensure data security and quality standards are met. Their role often involves strategic planning to enable data-driven decision making across the company.

What are the key skills and qualifications needed to thrive as a manager data engineering?

To thrive as a Manager Data Engineering, you need expertise in data architecture, advanced analytics, and leadership, typically supported by a degree in computer science or a related field. Familiarity with big data tools (like Hadoop, Spark), data warehousing systems, cloud platforms (AWS, Azure), and certifications such as AWS Certified Data Analytics are highly valued. Strong communication, problem-solving, and team management skills help drive project success and foster collaboration. These skills ensure effective data solutions, alignment with business goals, and the ability to lead and grow high-performing engineering teams.

How does a manager data engineering typically collaborate with data scientists and business stakeholders?

A Manager of Data Engineering often serves as a bridge between technical teams and business stakeholders. They work closely with data scientists to ensure that data pipelines and infrastructure meet analytical needs, while also translating business requirements into actionable engineering solutions. Regular coordination meetings, clear documentation, and cross-functional projects are common, enabling seamless collaboration and alignment on goals. This role requires strong communication skills and the ability to balance technical priorities with business objectives.

What is the difference between Manager Data Engineering vs Data Engineer?

AspectManager Data EngineeringData Engineer
Required CredentialsBachelor's or Master's in CS, Data Science, or related; often leadership experienceBachelor's or higher in CS, IT, or related; technical certifications optional
Work EnvironmentTeam leadership, project management, strategic planningData pipeline development, coding, data modeling
Employer & Industry UsageTech companies, finance, healthcare, where data teams are commonData-focused roles across various industries

The main difference is that Manager Data Engineering oversees data teams and projects, focusing on strategy and leadership, while Data Engineers handle the technical implementation of data pipelines and infrastructure. Managers typically have more experience and leadership skills, whereas Data Engineers are more hands-on with coding and data architecture.

What are the most commonly searched types of Data Engineering jobs in Nebraska?

The most popular types of Data Engineering jobs in Nebraska are:

What are popular job titles related to Manager Data Engineering jobs in Nebraska?

For Manager Data Engineering jobs in Nebraska, the most frequently searched job titles are:

What job categories do people searching Manager Data Engineering jobs in Nebraska look for?

The top searched job categories for Manager Data Engineering jobs in Nebraska are:

What cities in Nebraska are hiring for Manager Data Engineering jobs?

Cities in Nebraska with the most Manager Data Engineering job openings:

Manager Data Engineering jobs near you
Infographic showing various Manager Data Engineering job openings in Nebraska as of August 2026, with employment types broken down into 84% Full Time, 15% Part Time, and 1% Contract. Highlights an 79% Physical, 3% Hybrid, and 18% Remote job distribution, with an average salary of $92,623 per year, or $44.5 per hour.

Data Engineer 2

Fashion Institute of Design & Merchandising

Omaha, NE • On-site

$80 - $100/hr

Other

Posted 2 days ago

New

Job description

At HDR, we are committed to the principles of employment equity. We are an affirmative action and equal opportunity employer and consider all qualified applicants, regardless of criminal histories, arrest, and conviction records.

Job Responsibilities
  • Build and maintain batch and streaming ingestion pipelines from source systems into the enterprise data platform.
  • Implement robust error handling, retries, and recovery patterns to improve reliability.
  • Collaborate with platform teams on connectivity, access, and operational readiness.
  • Develop transformation models using a layered structure (raw, conformed, curated) to separate concerns and improve maintainability.
  • Use dependency management patterns to ensure correct build order and reproducible transformations.
  • Leverage shared code and reusable components to standardize patterns, reduce duplication, and enforce consistent logic.
  • Implement incremental processing where appropriate to reduce runtime and warehouse cost.
  • Implement data quality tests (e.g., unique, not_null, accepted_values) on critical models and key business entities.
  • Configure and monitor source freshness expectations for important upstream datasets.
  • Maintain model and column-level documentation; publish documentation and lineage to enable impact analysis and change management.
  • Integrate transformations into CI/CD workflows (build, test, docs generation) before promotion to higher environments.
  • Participate in code reviews, follow branching standards, and adhere to quality gates and approval processes.
  • Support release and rollback practices to maintain stability and reduce risk.
  • Tune transformations for performance and efficiency; partner with stakeholders to manage cost impacts.
  • Support monitoring and alerting for pipelines and transformations; respond to incidents and perform root cause analysis.
  • Document operational procedures and contribute to runbooks/playbooks.
Preferred Qualifications
  • Hands‑on experience with dbt Cloud or dbt Core in Git‑integrated workflows.
  • Experience with orchestration tools (e.g., Airflow, Dagster, Prefect) and scheduling patterns.
  • Experience implementing CI/CD quality gates for data (tests, linting, docs artifacts).
Required Qualifications
  • Bachelor’s degree in Computer Science, Information Systems, Data Engineering, or equivalent practical experience.
  • Minimum 3 years of experience in data engineering, data integration, or related roles.
  • Proven SQL proficiency and experience building transformations and pipelines.
  • Familiarity with cloud data platforms and modern ELT patterns.
Location

Primary Location

Schedule

Full‑time

Employee Status

Regular

Job Posting

May 27, 2026

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