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Data Analytics Engineer Jobs in Wisconsin (NOW HIRING)

Data Engineer (Hybrid)

Cottage Grove, WI ยท On-site

$108K - $130K/yr

As a Data Engineer, you'll play a critical role in shaping and executing Summit's data strategy ... Analyze complex datasets to identify trends, answer business questions, and support informed ...

Data Engineer

Milwaukee, WI ยท On-site

$112K - $135K/yr

The Data Engineer is responsible for the comprehensive data and reporting infrastructure at ... Minimum of 3 years' experience in data analytics or data solutions Demonstrated experience writing ...

Bachelor's degree in Data Science, Computer Science, Industrial Engineering, Statistics, or a related field. Work Experience * 5+ years in data analytics, with at least 3 years in a senior or lead ...

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Senior Associate & Summary The Opportunity As a Data Engineer - Senior Associate, you will focus on designing and ...

Big Data Engineer, Senior

Milwaukee, WI ยท On-site

$55 - $72.75/hr

Perform in-depth data quality analysis, identifying and resolving anomalies, inconsistencies, and errors to maintain data integrity. Work closely with developers, analysts, and client-facing teams to ...

... analytics environment, and the use of open-source tools, cloud computing, machine learning and data visualization and appropriate, relevant programming languages. *This is not a remote role, the ...

Partner with technical resources (e.g., developers, data engineers) to communicate business and ... Bachelor's degree in Information Systems, Data Analytics, Computer Science, Finance, Business, or a ...

Partner with technical resources (e.g., developers, data engineers) to communicate business and ... Bachelor's degree in Information Systems, Data Analytics, Computer Science, Finance, Business, or a ...

In this role, you will analyze server and infrastructure capacity trends, model future demand, and ... The Data Center Capacity Engineer is responsible for planning and delivering the end-to-end server ...

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Showing results 1-20

Data Analytics Engineer information

See Wisconsin salary details

$44.9K

$130.9K

$179.2K

How much do data analytics engineer jobs pay per year?

As of Jul 14, 2026, the average yearly pay for data analytics 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.

How do Data Analytics Engineers typically collaborate with data scientists and business stakeholders on projects?

Data Analytics Engineers play a crucial role in bridging the gap between raw data and actionable insights by building, optimizing, and maintaining data pipelines. They often work closely with data scientists to ensure data is clean, accessible, and structured for advanced analytics or machine learning models. Additionally, they collaborate with business stakeholders to understand reporting requirements and ensure that data solutions align with organizational objectives. Regular communication and cross-functional teamwork are essential aspects of this role, as engineers must translate business needs into technical specifications and deliver reliable data products.

Can a data engineer make 200k?

Data engineers can earn $200,000 or more annually, especially with experience, advanced skills in cloud platforms, big data tools, and certifications. Salaries vary by location, industry, and company size, with senior roles and those in high-demand markets more likely to reach or exceed this level.

What engineers make $500,000?

Senior data analytics engineers with extensive experience, advanced skills in data modeling, machine learning, and proficiency with tools like Python, SQL, and cloud platforms can reach salaries of $500,000 or more, especially in high-cost-of-living areas or within large tech companies. Achieving this level often requires a combination of technical expertise, leadership roles, and sometimes equity compensation.

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

To thrive as a Data Analytics Engineer, you need strong proficiency in data modeling, SQL, and statistical analysis, typically supported by a degree in computer science, statistics, or a related field. Familiarity with tools such as Python, R, Apache Spark, Tableau, and cloud data platforms like AWS or Google BigQuery is essential, along with relevant certifications. Excellent problem-solving, communication, and collaboration skills help you translate data insights into actionable business solutions. These skills and qualities are crucial for designing robust data pipelines and enabling data-driven decision-making across organizations.

Is 40 too late for data science?

Data Analytics Engineers and data science professionals can successfully transition into the field at age 40 or older, as skills such as programming, statistical analysis, and experience with tools like Python or SQL are valuable regardless of age. Many employers value diverse experience and lifelong learning, and certifications or online courses can help enhance credentials at any age.

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

AspectData Analytics EngineerData Scientist
CredentialsBachelor's or master's in CS, Data Science, or related fields; certifications like Google Data AnalyticsBachelor's or master's in CS, Statistics, or related fields; certifications like Certified Data Scientist
Work EnvironmentFocus on building data pipelines, dashboards, and analytics toolsFocus on statistical modeling, machine learning, and data exploration
Employer & Industry UsageUsed across tech, finance, healthcare for data infrastructure and analyticsCommon in research, product development, and advanced analytics teams

While both roles work with data, Data Analytics Engineers primarily develop data infrastructure and tools for analysis, whereas Data Scientists focus on statistical modeling and machine learning to generate insights. They often collaborate but have distinct technical focuses.

What does a data analytics engineer do?

A data analytics engineer designs, builds, and maintains data pipelines and systems to collect, process, and analyze large datasets. They use tools like SQL, Python, and cloud platforms to enable data-driven decision-making and often collaborate with data scientists and business teams to deliver actionable insights.
What are the most commonly searched types of Data Analytics Engineer jobs in Wisconsin? The most popular types of Data Analytics Engineer jobs in Wisconsin are:
Principal Data Analyst

Principal Data Analyst

Continuus Technologies LLC

Germantown, WI โ€ข On-site

Full-time

Posted 4 days ago


Job description

Role Overview

The Principal Data Analyst is a strategic analytics leader and subject-matter expert who shapes how data is used across the organization. This role leads the most complex, high-impact analyses, defines analytical standards, and partners with executive leadership to influence long-term business strategy. The Principal Data Analyst operates with broad autonomy and serves as a mentor and thought leader across the analytics community.

Key Responsibilities
  • Lead enterprise-level, high-impact analyses that inform strategic decisions

  • Define and govern company-wide KPIs, metrics, and analytical frameworks

  • Translate ambiguous, complex business problems into structured analytical approaches

  • Influence executive decision-making through clear, compelling data storytelling

  • Partner with senior leadership to shape analytics strategy and priorities

  • Set standards for analytical rigor, experimentation, and data interpretation

  • Mentor Staff and Senior Analysts and elevate analytical excellence across teams

  • Drive improvements in data quality, metric consistency, and governance

  • Identify emerging trends, risks, and opportunities proactively

Qualifications
  • Bachelor's degree in Data Analytics, Statistics, Economics, Business, or related field (or equivalent experience)

  • 10+ years of experience in analytics or data-focused roles

  • Expert-level SQL and advanced analytical modeling skills

  • Extensive experience with BI and visualization platforms (Tableau, Power BI, Looker, etc.)

  • Strong statistical reasoning and business acumen

  • Proven ability to influence executive stakeholders through insights

Preferred Experience
  • Advanced proficiency in Python or R for analysis

  • Experience designing experimentation or causal analysis frameworks

  • Familiarity with data engineering and modern data architectures

  • Domain expertise (e.g., product, finance, HR, operations, growth analytics)

  • Experience shaping analytics strategy without direct people management