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Data Analytics Engineer Jobs in Wisconsin (NOW HIRING)

Data & Analytics Engineer

Milwaukee, WI · On-site

$112K - $135K/yr

Are you looking for an opportunity to expand your expertise in analytics engineering, data modeling, and modern cloud data platforms in an environment that values curiosity and continuous learning?

Data & Analytics Engineer

Milwaukee, WI · Hybrid

$112K - $135K/yr

Are you looking for an opportunity to expand your expertise in analytics engineering, data modeling, and modern cloud data platforms in an environment that values curiosity and continuous learning?

Data & Analytics Engineer

Milwaukee, WI · On-site

$112K - $135K/yr

Are you looking for an opportunity to expand your expertise in analytics engineering, data modeling, and modern cloud data platforms in an environment that values curiosity and continuous learning?

Role Overview This role is designed as a modern hybrid data position that sits between traditional analytics, BI development, and engineering. Rather than hiring a narrowly scoped reporting analyst ...

Role Overview This role is designed as a modern hybrid data position that sits between traditional analytics, BI development, and engineering. Rather than hiring a narrowly scoped reporting analyst ...

The Analytics Engineer at Client partners closely with business teams to design and deliver data solutions that drive decision-making, including advanced Power BI dashboards, Power Apps, and Alteryx ...

At Delta Defense, data powers a mission much larger than technology. At Delta Defense, data isn't just about reporting-it's about impact. As an Analytics Engineer , you'll transform complex data into ...

At Delta Defense, data powers a mission much larger than technology. At Delta Defense, data isn't just about reporting--it's about impact. As an Analytics Engineer , you'll transform complex data ...

Manages and leads a team of data analysts, engineers, business intelligence specialists, and innovation experts to deliver high-quality, data-driven solutions, while overseeing ongoing support.

The IT Manager, Data & Analytics owns and governs Komatsu's enterprise data and analytics platforms, including Palantir Foundry, Microsoft Power BI, Azure Synapse, and associated data engineering ...

... analysts, engineers, business intelligence specialists, and innovation experts to deliver high-quality, data-driven solutions, while overseeing ongoing support. • Advises business leaders by ...

BI Analytics Engineer

Milwaukee, WI

$50.25 - $65.25/hr

As a BI Analytics Engineer at Uline, you'll turn data into insights that drive decisions across the business. Partner with teams across the company to design dashboards, shape reporting and build ...

BI Analytics Engineer

Pleasant Prairie, WI

$49.50 - $64.25/hr

As a BI Analytics Engineer at Uline, you'll turn data into insights that drive decisions across the business. Partner with teams across the company to design dashboards, shape reporting and build ...

BI Analytics Engineer

Pleasant Prairie, WI · On-site

$49.50 - $64.25/hr

As a BI Analytics Engineer at Uline, you'll turn data into insights that drive decisions across the business. Partner with teams across the company to design dashboards, shape reporting and build ...

BI Analytics Engineer

Kenosha, WI

$49.75 - $64.75/hr

As a BI Analytics Engineer at Uline, you'll turn data into insights that drive decisions across the business. Partner with teams across the company to design dashboards, shape reporting and build ...

$211K - $246K/yr

Define the data engineering and analytics roadmap, aligned with company goals. This includes prioritizing data platform investments, reporting needs, analytics capabilities, and cross-functional data ...

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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:
Data & Analytics Engineer

Data & Analytics Engineer

Baird

Milwaukee, WI • On-site

$112K - $135K/yr

Full-time

Posted 5 days ago


Baird rating

8.6

Company rating: 8.6 out of 10

Based on 8 frontline employees who took The Breakroom Quiz


Job description

About the Role:
Are you energized by transforming complex financial services data into meaningful insights that influence real business decisions? Do you enjoy blending hands-on technical work with close collaboration across business teams? Are you looking for an opportunity to expand your expertise in analytics engineering, data modeling, and modern cloud data platforms in an environment that values curiosity and continuous learning?
As Baird continues to invest in data as a strategic asset, we are adding a Data & Analytics Engineer to our growing IT Data Team. In this role, you'll play a meaningful part in shaping how financial services data is structured, transformed, and delivered to drive smarter decision-making across the firm. You'll contribute to building scalable, high-quality data solutions while partnering closely with stakeholders to turn evolving business needs into actionable insights.
This is an excellent opportunity for a data professional who thrives in a collaborative, agile environment and enjoys solving complex problems while delivering incremental value. You'll gain exposure to modern data tools and practices, work alongside experienced engineers and architects, and continuously grow your technical and business acumen.
This position is hybrid, offering a combination of 2 day/week remote work and 3 days/week in our collaborative downtown Milwaukee workspace. At Baird, you'll find a supportive culture centered on teamwork, continuous learning, and making a meaningful impact through data.
The Impact You'll Make:
Data Engineering & Data Management:
  • Contribute to the design, build, and maintenance of data pipelines that ingest and transform financial services data
  • Apply data modeling skills (3NF and dimensional) to support analytics-ready datasets
  • Perform data analysis and profiling to understand source data and support quality outcomes
  • Develop and validate source-to-target mappings and transformation logic
  • Implement and test end-to-end data solutions under the guidance of senior engineers
  • Follow established practices to ensure sensitive data is protected and handled appropriately

Analytics Enablement & Delivery:
  • Support data discovery efforts and help prototype datasets that bring together multiple data sources
  • Leverage existing tools to enable reporting and visualization for financial services users
  • Document datasets and transformations to support usability and adoption
  • Deliver work incrementally while balancing changing priorities

Collaboration, Learning & Growth:
  • Collaborate with delivery team members, architects, and business partners
  • Communicate clearly about progress, risks, and dependencies
  • Learn and apply Baird data standards, tools, and best practices
  • Seek feedback and coaching from senior Data & Analytics Engineers
  • Continuously build skills through training, documentation, and hands-on experience

What You'll Bring to Baird:
  • 5-7 years of experience delivering data and analytics solutions in a collaborative environment
  • Experience in data engineering, analytics engineering, business intelligence development, or a related data-focused role
  • Strong SQL skills and familiarity with relational database concepts and best practices
  • Experience performing data analysis, profiling, validation, and troubleshooting to support reliable data solutions
  • Ability to partner effectively with business stakeholders to understand requirements and support analytics needs
  • Strong problem-solving skills, intellectual curiosity, and a desire to continuously grow technical expertise
  • Experience with databases and platforms such as SQL Server, Snowflake, Azure SQL Database, and Azure Data Lake
  • Experience with data integration tools such as SSIS, dbt, Azure Data Factory, or similar technologies
  • Experience writing queries and developing solutions using SQL, T-SQL, Azure Data Studio, or similar tools
  • Familiarity with BI and analytics tools such as Power BI, Alteryx, or comparable platforms
  • Working knowledge of data modeling and governance concepts, including 3NF, dimensional modeling, data mapping, data profiling, and data quality practices
  • Experience working with common data formats such as CSV, JSON, XML, and Parquet
  • Experience working in a regulated or data-sensitive environment is preferred
  • Bachelor's degree in Computer Science, MIS, Business Administration, Finance, or equivalent experience

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