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Data Engineer Jobs in Wisconsin (NOW HIRING)

AgSource

Sr. Data Engineer

Madison, WI · On-site

$114K - $137K/yr

The ideal candidate will possess expertise in Databricks and modern data engineering tools such as Azure Data Factory, combined with hands on experience working with biological, genomic, or other ...

Urus Group LP

Sr. Data Engineer

Madison, WI · On-site

$115K - $138K/yr

The ideal candidate will possess expertise in Databricks and modern data engineering tools such as Azure Data Factory, combined with hands on experience working with biological, genomic, or other ...

Pwc

Data Engineer - Senior Manager

Milwaukee, WI

$124K - $280K/yr

In data engineering at PwC, you will focus on designing and building data infrastructure and systems to enable efficient data processing and analysis. You will be responsible for developing and ...

Old National Bank

Data Engineer Lead

Milwaukee, WI · On-site

$98K - $199K/yr

Data Engineer Lead Job Locations US-MN-Lake Elmo | US-IL-Chicago | US-IN-Evansville | US-WI-Milwaukee Category/Function Information Technology Position Type Regular Full-Time Requisition ID 2026 ...

Pwc

Data Engineer - Senior Associate

Milwaukee, WI

$77K - $202K/yr

In data engineering at PwC, you will focus on designing and building data infrastructure and systems to enable efficient data processing and analysis. You will be responsible for developing and ...

Fielmann USA

Data Engineer II

Green Bay, WI · On-site

$111K - $133K/yr

... data engineering, information systems, or related field or equivalent experience; master's degree preferred • 5+ years of hands-on experience in data engineering or related roles • Professional ...

ULINE

Senior Data Engineer

Kenosha, WI · On-site

$96K - $148K/yr

Senior Data Engineer Pay from $96,000 to $148,000 per year 2200 S. Lakeside Drive, Waukegan, IL 60085 Fuel the future of data engineering and analytics for our growing North American company! As a ...

ULINE

Senior Data Engineer

Kenosha, WI · On-site

$96K - $148K/yr

Senior Data Engineer Pay from $96,000 to $148,000 per year 2200 S. Lakeside Drive, Waukegan, IL 60085 Fuel the future of data engineering and analytics for our growing North American company! As a ...

ULINE

Senior Data Engineer

Pleasant Prairie, WI · On-site

$96K - $148K/yr

Senior Data Engineer Pay from $96,000 to $148,000 per year 2200 S. Lakeside Drive, Waukegan, IL 60085 Fuel the future of data engineering and analytics for our growing North American company! As a ...

ULINE

Senior Data Engineer

Pleasant Prairie, WI · On-site

$96K - $148K/yr

Senior Data Engineer Pay from $96,000 to $148,000 per year 2200 S. Lakeside Drive, Waukegan, IL 60085 Fuel the future of data engineering and analytics for our growing North American company! As a ...

Pwc

Data Engineer - Manager

Milwaukee, WI

$99K - $232K/yr

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Manager & Summary The Opportunity As a Data Engineer - Manager, you will play a pivotal role in transforming raw data ...

Robert Half

Senior Data Engineer

Madison, WI · On-site

$155K - $175K/yr

We are seeking a Senior Data Engineer to design, build, and optimize modern cloud-based data platforms. This role is responsible for developing scalable data pipelines, supporting enterprise ...

Exact Sciences

Sr. Data Engineer

Madison, WI · On-site

$115K - $138K/yr

As a Senior Data Engineer, this seasoned professional will demonstrate competence and creativity in a wide range of technical areas. This role will have a lead role in the design, development, and ...

New

Exactsciences

Sr. Data Engineer

Madison, WI · On-site

$115K - $138K/yr

As a Senior Data Engineer, this seasoned professional will demonstrate competence and creativity in a wide range of technical areas. This role will have a lead role in the design, development, and ...

New

Fiserv, Inc.

Big Data Engineer, Senior

Milwaukee, WI · On-site

$55 - $72.75/hr

Big Data Engineer, Senior EMPLOYER: Fiserv Solutions, LLC LOCATION: Milwaukee, WI (and various unanticipated locations throughout the US subject to authorization from management) DUTIES: Design ...

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Showing results 1-20

All JobsData Engineer JobsData Engineer Jobs in Wisconsin

Data Engineer information

See Wisconsin salary details

$44.9K

$130.9K

$179.2K

How much do data engineer jobs pay per year?

As of Jul 13, 2026, the average yearly pay for data engineer in Wisconsin is $130,930.00, according to ZipRecruiter salary data. Most workers in this role earn between $115,600.00 and $138,800.00 per year, depending on experience, location, and employer.

Is a data engineer a difficult job?

A data engineer role involves designing, building, and maintaining data pipelines and infrastructure, which requires strong programming skills, knowledge of databases, and familiarity with tools like SQL, Python, and cloud platforms. The job can be challenging due to the complexity of managing large-scale data systems and ensuring data quality and security, but it is manageable with proper training and experience.

What is the difference between Data Engineer vs Data Scientist?

AspectData EngineerData Scientist
Primary FocusBuilding and maintaining data pipelines and infrastructureAnalyzing data to extract insights and create models
SkillsSQL, ETL, programming (Python, Java), database managementStatistics, machine learning, data analysis, programming (Python, R)
Work EnvironmentData warehouses, cloud platforms, backend systemsData analysis environments, research labs, visualization tools
Common ToolsApache Spark, Hadoop, Airflow, SQLJupyter, RStudio, Tableau, scikit-learn

Data Engineers focus on creating and maintaining the infrastructure that allows data to be collected, stored, and processed efficiently. Data Scientists analyze this data to generate insights, build predictive models, and support decision-making. While their skills overlap, Data Engineers are more involved in data pipeline development, whereas Data Scientists focus on data analysis and modeling.

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 a strong background in computer science, data modeling, and programming languages such as Python or Java, often coupled with a relevant degree. Familiarity with ETL tools, big data frameworks (like Hadoop or Spark), and cloud platforms (such as AWS or Azure) is typically required, along with certifications like AWS Certified Data Analytics. Strong problem-solving skills, attention to detail, and effective communication set exceptional data engineers apart. These skills and qualities are essential for building robust data pipelines, ensuring data quality, and supporting data-driven decision-making across organizations.

What Does a Data Engineer Do?

The job duties of a data engineer involve helping with the development of systems, software, and infrastructure used to process, store and analyze data. Your responsibilities in this career include working to install data management software. Your employer may expect you to perform maintenance and install updates to all software and systems that they use for data acquisition, management, and analysis. Data engineers also analyze existing data systems to find ways to improve efficiency and accessibility. You then suggest upgrades or changes based on your assessment.

What are Data Engineers?

Data Engineers are IT professionals who design, construct, install, and maintain large-scale processing systems and other infrastructure for collecting, storing, and analyzing data. They build and optimize data pipelines and architectures that allow organizations to efficiently access and use data for business insights. Data Engineers work closely with data scientists, analysts, and other stakeholders to ensure that data is reliable, accessible, and secure. Their responsibilities often include working with databases, cloud platforms, and big data tools.

How do Data Engineers typically collaborate with Data Scientists and Analysts within an organization?

Data Engineers play a crucial role in ensuring that Data Scientists and Analysts have reliable, well-structured data for their projects. This collaboration often involves building and maintaining data pipelines, optimizing data storage solutions, and troubleshooting data quality issues. Regular communication and agile teamwork are common, with Data Engineers frequently participating in meetings to understand analytical requirements and adjust data processes accordingly. By working closely together, these teams can quickly iterate on data models and deliver actionable insights to drive business decisions.

What does a data engineer actually do?

A data engineer designs, builds, and maintains the infrastructure and pipelines that enable organizations to collect, store, and process large volumes of data. They work with tools like SQL, Python, and cloud platforms to ensure data is accessible, reliable, and ready for analysis by data scientists and analysts.

Is a data engineer entry level?

Data engineering is typically an intermediate to senior role that requires experience with programming, databases, and data pipelines. Entry-level positions may be available for those with relevant internships, certifications, or strong foundational skills in SQL, Python, or cloud platforms, but most roles expect prior experience or demonstrated technical competence.

What engineer makes $500,000 a year?

Senior data engineers with extensive experience, advanced skills in big data tools, and certifications can earn salaries approaching or exceeding $500,000 annually, especially in high-cost-of-living areas or within large tech companies. Such compensation often includes bonuses, stock options, and other incentives. These roles typically require strong programming, cloud platform expertise, and a deep understanding of data architecture.
More about Data Engineer jobs
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Data Engineer jobs near you
Sr. Data Engineer

Sr. Data Engineer

AgSource

Madison, WI • On-site

$114K - $137K/yr

Full-time

Re-posted 16 days ago

Job description


This role is responsible for the design, development, and maintenance of data integration, analytics, and reporting solutions that support our animal genetics and bioinformatics workloads. The ideal candidate will possess expertise in Databricks and modern data engineering tools such as Azure Data Factory, combined with hands on experience working with biological, genomic, or other omics datasets. This position requires a proactive, self-motivated, and results-oriented individual with a passion for data, a strong understanding of data architecture and warehousing principles, and an appreciation for bioinformatics workflows in a commercial genetics environment.
Responsibilities
Data Integration
  • Design, develop, and maintain robust and efficient ETL/ELT pipelines and processes on Databricks for both operational and bioinformatics datasets (e.g., genomic markers, phenotypic data, laboratory outputs).
  • Ingest, transform, and harmonize structured and semi-structured biological data from lab systems, LIMS, sequencing platforms, and external partners into the enterprise data platform.
  • Troubleshoot and resolve Databricks pipeline errors and performance issues.
  • Optimize data flow performance and minimize data latency across scientific and business use cases.
  • Implement data quality checks, validations, and reconciliation processes within ETL workflows, including domain-specific checks for genomic and phenotypic data.

Databricks Development
  • Develop and maintain Databricks pipelines, notebooks, and datasets using Python, Spark, and SQL.
  • Optimize Databricks jobs for performance and cost-effectiveness, including largescale bioinformatics and analytics workloads.
  • Integrate Databricks with other data sources and systems, including lab instruments, genomic databases, and on-prem or cloud data stores.
  • Participate in the design and implementation of data lake architectures that support both traditional analytics and bioinformatics pipelines.

Data Warehousing
  • Participate in the design and implementation of data warehousing solutions to support reporting, analytics, and scientific modeling.
  • Model and curate subject areas for genetics, reproduction, and bioinformatics (e.g., animals, pedigrees, genotypes, breeding values, trials).
  • Support data quality initiatives and implement data cleansing procedures across business and scientific domains.

Reporting and Analytics
  • Collaborate with business users, scientists, geneticists, and bioinformaticians to understand data requirements for department-driven reporting and analytics needs.
  • Maintain and extend the existing library of complex dashboards and visualizations to surface genetic, reproductive, and operational insights.
  • Enable self-service analytics for R&D and product teams by exposing well- governed, documented data products.
  • Troubleshoot and resolve report issues, including performance bottlenecks and data inconsistencies.

Cloud Platform Experience
  • Apply strong programming skills in Python, SQL, and Spark to build scalable data and bioinformatics workflows.
  • Use CI/CD and IaC tools (Terraform, ARM, CloudFormation) to automate deployment of data platform components and analytics environments.
  • Design and implement Databricks platform architecture on Azure and AWS infrastructure, including environments that support largescale scientific computation.
  • Contribute to cloud security, governance, and cost optimization practices for data and bioinformatics workloads.

Bioinformatics and Scientific Collaboration
  • Partner with geneticists, biostatisticians, and bioinformaticians to translate scientific requirements into scalable data and platform architectures.
  • Support or orchestrate bioinformatics pipelines (e.g., variant processing, quality control, annotation, genotype imputation, genomic evaluation) using cloud and Databricks capabilities.
  • Ensure that data models, pipelines, and storage structures meet the needs of downstream analytics, predictive models, and genetic evaluations.
  • Advocate for best practices in managing sensitive biological and genetic data, including data governance, access control, and compliance with relevant standards and regulations.

Collaboration and Communication
  • Thrive in an entrepreneurial, self-starting, and fast-paced environment, working both independently and with our highly skilled teams.
  • Collaborate effectively with business users, data analysts, scientists, and other IT teams.
  • Communicate technical information clearly and concisely, both verbally and in writing, to technical and nontechnical stakeholders.
  • Document all development work, data models, and procedures thoroughly, including bioinformatics and scientific data flows.

Continuous Growth
  • Keep abreast of the latest advancements in data integration, cloud platforms, bioinformatics tooling, and data engineering technologies.
  • Continuously improve skills and knowledge through training and self-learning in both data engineering and bioinformatics domains.

Requirements
  • Bachelor's degree in Computer Science, Information Systems, Bioinformatics, Computational Biology, or a related field; a Master's degree is an asset.
  • 7+ years of experience in data integration and reporting, with experience designing and operating cloud-based data platforms.
  • Extensive experience with Databricks, including Python, Spark, and Delta Lake.
  • Strong proficiency with relational databases (e.g., SQL Server, RDS), including TSQL, stored procedures, and functions.
  • Experience with data warehousing concepts and best practices.
  • Experience with Microsoft Azure cloud platform; exposure to Microsoft Fabric is desirable.
  • Hands on experience working with biological, genomic, or other omics datasets in a bioinformatics or life sciences setting (e.g., sequence data, SNP arrays, GWAS outputs, phenotypic traits).
  • Familiarity with common bioinformatics tools, data formats (e.g., FASTQ, VCF, PLINK), and workflows is highly desirable.
  • Strong analytical and problem-solving skills, with the ability to reason about complex data and scientific requirements.
  • Excellent communication and interpersonal skills.
  • Ability to work independently and as part of a cross-functional team across IT, science, and business.
  • Experience with Agile methodologies.
  • Demonstrated background in bioinformatics or computational biology, preferably supporting genetics, breeding, or life science research in an applied or commercial context.
  • Must be legally authorized to work in the United States.

About Us
As a holding company with cooperative and private ownership, URUS is a family of businesses at the heart of the dairy and beef industry - Alta Genetics, GENEX, Genetics Australia, Leachman Cattle, Jetstream, PEAK, SCCL, Trans Ova Genetics and VAS. Each organization has its unique identity, products, and services. These companies work globally to provide cutting-edge dairy and beef genetics, customized reproductive services to maximize conceptions, dairy management information to take producers to the frontline of progressive dairy farming, and an array of products and services to help bovines reach their full genetic potential. URUS has 9 brands in 17 retail countries and employs nearly 2,800 people globally.

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