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Data Engineer With Jobs in Nebraska (NOW HIRING)

DMSi Software

Sr Data Engineer

Omaha, NE

$96K - $130K/yr

You'll work within DMSi's broader architectural ecosystem, collaborating closely with Systems Engineering, Information Security, and the Architecture teams. As the expert voice for data, you'll ...

Centric Consulting

Data / ML Engineer

Omaha, NE · Hybrid

$109K - $131K/yr

Data / ML Engineer Job Level: W2T Consultant Job Location: Hybrid/Onsite-Must be a local candidate ... Enjoy the people you work with, have fun, and do great work. These principles define our consulting ...

Snowrelic Inc

ETL Data Engineer (W2 Full Time)

Omaha, NE · On-site

$109K - $131K/yr

Role: Data Engineer; Operational Data Group Location: Onsite in Omaha, Nebraska Department ... You will work with modern tools and data platforms to support critical decision-making across the ...

HDR

Senior Data Engineer

Omaha, NE · On-site

$101K - $137K/yr

... with platform/security to ensure access, tagging/classification, and governance alignment. • ... Data Engineering, or other applicable degree. • Minimum 6 years of data engineering experience ...

HDR

Senior Data Engineer

Omaha, NE · On-site

$101K - $137K/yr

Partner with platform/security to ensure access, tagging/classification, and governance alignment ... Minimum 6 years of data engineering experience with demonstrated delivery of complex pipelines and ...

Monitise

Senior Cloud Data Engineer

Omaha, NE · On-site

$101K - $137K/yr

Job Title Senior Cloud Data Engineer About your role: At Fiserv, we are dedicated to transforming ... You will work with cross-functional teams to deliver solutions that align with our business goals ...

Fiserv, Inc.

Senior Cloud Data Engineer

Omaha, NE · On-site

$101K - $137K/yr

Job Title Senior Cloud Data Engineer About your role: At Fiserv, we are dedicated to transforming ... You will work with cross-functional teams to deliver solutions that align with our business goals ...

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What are Data Engineers?

Data Engineers are professionals who design, build, and maintain the infrastructure and systems needed to collect, store, and analyze large amounts of data. They work with tools and technologies that enable organizations to process data efficiently and ensure its quality, reliability, and accessibility. Data Engineers often collaborate with data scientists, analysts, and other IT professionals to support business intelligence and analytical needs. Their work is crucial for turning raw data into actionable insights.

What are the key skills and qualifications needed to thrive as a Data Engineer, and why are they important?

To thrive as a Data Engineer, you need expertise in SQL, data modeling, ETL processes, and strong programming skills in languages like Python or Java, often supported by a degree in computer science or a related field. Familiarity with big data technologies such as Hadoop, Spark, and cloud platforms like AWS or Azure, as well as relevant certifications, is highly valued. Strong problem-solving abilities, attention to detail, and effective communication skills help Data Engineers collaborate with stakeholders and troubleshoot complex issues. These competencies ensure efficient data pipeline development, reliable data infrastructure, and support data-driven decision-making in organizations.

What are some common challenges Data Engineers face when working with large-scale data pipelines, and how can they be addressed?

Data Engineers often encounter challenges such as data quality issues, pipeline bottlenecks, and scalability concerns when managing large-scale data pipelines. Addressing these challenges typically involves implementing robust data validation checks, optimizing ETL processes for efficiency, and leveraging scalable cloud-based solutions like AWS, Azure, or Google Cloud. Additionally, collaborating closely with data analysts, data scientists, and DevOps teams helps ensure smooth data flow and timely resolution of issues. Continuous monitoring, documentation, and automation are also key practices for maintaining reliable and efficient pipelines.

What is the difference between Data Engineer With vs Data Scientist?

AspectData Engineer WithData Scientist
Required CredentialsBachelor's in CS, Engineering, or related field; certifications like AWS, GCP, or AzureBachelor's or higher in CS, Statistics, or related; often with certifications in data analysis or machine learning
Work EnvironmentBuild and maintain data pipelines, databases, and infrastructureAnalyze data, develop models, and generate insights
Employer & Industry UsageTech companies, finance, healthcare, where data infrastructure is criticalResearch institutions, tech firms, marketing, and analytics-focused companies

While Data Engineers With focus on developing and maintaining data infrastructure, Data Scientists analyze data to derive insights. Both roles often collaborate but serve different functions within data teams.

What are popular job titles related to Data Engineer With jobs in Nebraska? For Data Engineer With jobs in Nebraska, the most frequently searched job titles are:
What job categories do people searching Data Engineer With jobs in Nebraska look for? The top searched job categories for Data Engineer With jobs in Nebraska are:
What cities in Nebraska are hiring for Data Engineer With jobs? Cities in Nebraska with the most Data Engineer With job openings:
Data Engineer With jobs near you

Sr Data Engineer

DMSi Software

Omaha, NE

$96K - $130K/yr

Full-time

Posted 24 days ago

Job description

As part of our evolving Product strategy, DMSi seeks to expand our footprint of usable data at scale. DMSi creates and operates technology solutions to support the Building Materials industry. We want to offer uses for our data which serve future product initiatives, customer and business self-service needs, and broader industry needs. All the while, we intend to produce a cloud-based, multi-tenant, data environment which is responsive to the evolving nature of the data landscape and the industry.

As our Senior Data Engineer, you'll own the data pipeline that powers DMSi's next generation of data products—from enterprise data access to AI-powered analytics, building, scaling, and evolving our data pipeline, and shipping products that building materials professionals will use every day.

You'll work within DMSi's broader architectural ecosystem, collaborating closely with Systems Engineering, Information Security, and the Architecture teams. As the expert voice for data, you'll advocate for best practices and drive execution within those guardrails. 

 RESPONSIBILITIES AND DUTIES:

  1. Own the Data Pipeline
    • Design, build, and evolve the data pipelines that power DMSi's data products—working within our established stack (PostgreSQL, Kafka, dbt).
    • Drive technical decisions for scalable and performant data extraction, transformation, and delivery—selecting tools, evaluating build vs. buy, and establishing frameworks and processes.
    • Establish data governance standards and quality assurance practices.
    • Serve as DMSi's internal expert on data engineering best practices.
  2. Ship Products 
    • Launch multiple data products, including enterprise data access (PostgreSQL), event streaming (Kafka), and in-app analytics.
    • Build production-ready pipelines that deliver customer data reliably at scale in a multi-tenant environment.
    • Create a foundational data infrastructure to support AI and machine learning capabilities across DMSi's product portfolio.
    • Partner with Product to iterate quickly from customer feedback to deployed improvements.
  3. Collaborate Across Teams 
    • Work closely with Systems Engineering and Architecture to ensure data infrastructure integrates seamlessly with DMSi's broader technical operations.
    • Partner with Information Security to implement data security, access controls, and compliance requirements.
    • Provide technical leadership and mentorship to Data Engineers on the team.
    • Conduct code reviews that elevate quality and transfer knowledge across the organization.

KNOWLEDGE, SKILLS, AND ABILITIES:
5+ years of hands-on data engineering experience, with at least 2 years in a senior or lead capacity.
Deep expertise in SQL designing schemas, optimizing queries, and troubleshooting performance issues confidently.
Production experience building and maintaining data pipelines using modern tools (dbt strongly preferred; experience with Airflow, Meltano, Singer, or similar also valuable).
Strong Python skills for data processing, automation, and scripting.
Cloud infrastructure experience (AWS and GCP preferred: S3, Glue, Athena, Redshift, Lake Formation).
DevOps fluency—CI/CD pipelines, containerization, and infrastructure-as-code are familiar territory.
Collaborative mindset and strong communication skills.
Background in building data products or platforms (not just internal analytics).
Exposure to machine learning pipelines or feature stores.

EDUCATION AND EXPERIENCE: 
Bachelor's or Master’s Degree in Computer Science, Computer Engineering, Electrical Engineering, Management Information Systems, or related field preferred.
Well-experienced in working in Agile shop.

WORK ENVIRONMENT AND PHYSICAL DEMANDS:
Normal office environment with use of computers and telephone systems; no unusual physical demands.
Travel to customer locations including overnight, business air travel, and car rental.

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