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Data Engineer Jobs in Sheboygan, WI (NOW HIRING)

Owns the WasteLAB organization's master data collection and reporting. * Creates standardized ... data, engineering, codes & standards, and marketing). * Supports WasteLAB MFG process and NPD ...

Owns the WasteLAB organization's master data collection and reporting. * Creates standardized ... data, engineering, codes & standards, and marketing). * Supports WasteLAB MFG process and NPD ...

Owns the WasteLAB organization's master data collection and reporting. * Creates standardized ... data, engineering, codes & standards, and marketing). * Supports WasteLAB MFG process and NPD ...

Engineer, WasteLAB Materials

Kohler, WI · On-site

$83K - $127K/yr

Engineer, WasteLAB Materials Work Mode: Onsite Location: Onsite - Kohler, WI Opportunity Join ... Owns the WasteLAB organization's master data collection and reporting. * Creates standardized ...

Engineer, WasteLAB Materials

Kohler, WI · On-site

$83K - $127K/yr

Engineer, WasteLAB Materials Work Mode: Onsite Location:  Onsite - Kohler, WI Opportunity Join ... Owns the WasteLAB organization's master data collection and reporting. * Creates standardized ...

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Showing results 1-20

Data Engineer information

See Sheboygan, WI salary details

$44.3K

$129.3K

$176.9K

How much do data engineer jobs pay per year?

As of Jul 28, 2026, the average yearly pay for data engineer in Sheboygan, WI is $129,272.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,100.00 and $137,000.00 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.
What are the most commonly searched types of Data Engineer jobs in Sheboygan, WI? The most popular types of Data Engineer jobs in Sheboygan, WI are:
What job categories do people searching Data Engineer jobs in Sheboygan, WI look for? The top searched job categories for Data Engineer jobs in Sheboygan, WI are:
What cities near Sheboygan, WI are hiring for Data Engineer jobs? Cities near Sheboygan, WI with the most Data Engineer job openings:
Infographic showing various Data Engineer job openings in Sheboygan, WI as of July 2026, with employment types broken down into 92% Full Time, and 8% Contract. Highlights an 100% In-person job distribution, with an average salary of $129,272 per year, or $62.1 per hour.
Curriculum Manager - Data Science and AI

Curriculum Manager - Data Science and AI

DataCamp

Belgium, WI • On-site, Remote

Other

Medical, Dental, Vision

Posted 22 days ago


Job description

About DataCamp

Data and AI skills are critical for thriving today, and DataCamp is the platform that empowers everyone to learn them. We help individuals and Fortune 1000 companies close the data and AI skills gap through world-class learning, hands-on training, and a global community of expert instructors.

In this role, you'll collaborate with instructors and teams across curriculum, engineering, product, and marketing to expand and improve our Data Science and Data Engineering curriculum-helping millions worldwide upskill in data and AI.

About the role

This is an individual contributor role. You will collaborate with subject matter experts and leverage in-house-built cutting-edge AI tooling to scale high-quality course creation. Here's what your day-to-day will look like: 

  • Manage the entire content development lifecycle and deadlines.
  • Source and recruit top-tier subject-matter experts as instructors. 
  • Collaborate with instructors to create engaging content. 
  • Consistently leverage a variety of off-the-shelf and in-house AI systems to drive high-quality content production. 
  • Design, review, and create content on data science and data engineering. You will review content from a learner perspective, ensuring it is technically accurate and pedagogically effective.
  • Continuously assess course performance using learner feedback and engagement data to drive improvements.
  • Identify and prioritize existing curriculum gaps or new topics in data science and data engineering.

Qualifications:

  • A solid technical background in Python and SQL. A technical background in data engineering is a plus. 
  • Strong expertise in instructional design, with proven experience designing, structuring, and teaching technical courses, and creating interactive, hands-on learning experiences.
  • Graduate degree (Master's or PhD) in Computer Science, AI, Data Science, or a related STEM field, or equivalent industry experience with hands-on expertise in data science, machine learning, or software development.
  • Strong experience with agentic AI systems such as Claude Code, Cursor, Replit. You can demonstrate you've increased your output 10x with AI.

Bonus if you have the following

  • A deep understanding of the DataCamp course format-you have an intuitive understanding of what makes a great DataCamp course.
  • An existing network of potential subject matter experts who can become DataCamp instructors.
  • An extensive track record of building sophisticated AI systems and workflows.

Why Datacamp? 

Joining DataCamp means becoming part of a dynamic, creative, and international start-up. Here are just a few of the reasons why you'll love being on our team:

  • Exciting Challenges - Tackle some of the most important educational challenges in Data & AI.
  • Work with the Best Instructors - Partner with top-tier instructors from leading organizations like Microsoft, Hugging Face, AWS, and more.
  • Competitive Compensation - We offer a competitive salary with attractive benefits.
  • Work Flexibility - Benefit from flexible working hours and a remote-friendly culture.
  • Professional Growth - Access to a yearly learning & development budget.
  • Global Culture - Join a team that values international collaboration.
  • Annual Retreats - Participate in international company retreats, fostering a global team spirit.
  • Tools & Setup - Receive an annual IT equipment budget to refresh your workspace.

Our competitive compensation package offers additional benefits. On top of your salary you will also receive extra legal benefits such as best-in-class medical insurance including dental and vision. Depending on your location additional benefits might be available to you.