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Data Analytics Engineer Jobs in Wisconsin (NOW HIRING)

LRS

Senior Data & Analytics Engineer

Milwaukee, WI · On-site

$65 - $95/hr

... data architecture, modeling, engineering, and reporting. Key Responsibilities Partner with business leaders to understand analytics needs and define solution roadmaps Design scalable data and ...

MLG Capital

Analytics Engineer

Brookfield, WI

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 ...

MLG Capital

Analytics Engineer

Brookfield, WI · On-site

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 ...

Komatsu

IT Manager, Data & Analytics

Milwaukee, WI · On-site

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

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All JobsData Analytics Engineer JobsData Analytics Engineer Jobs in Wisconsin

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 Jun 15, 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 I be a data analyst in 3 months?

Becoming a data analyst in three months is challenging but possible with intensive study of core skills such as SQL, Excel, and data visualization tools like Tableau or Power BI. Success depends on prior experience, learning pace, and dedication, but typically, developing proficiency takes longer than three months for most individuals.

What engineers make $500,000?

Senior data analytics engineers with extensive experience, advanced skills in data modeling, and proficiency in tools like Python, SQL, and cloud platforms can earn $500,000 or more annually, 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 stock options or bonuses.

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 AI replacing data analysts?

AI is transforming the role of data analysts by automating routine tasks such as data cleaning and basic analysis, allowing analysts to focus on more complex insights and strategic decision-making. However, data analysts are still essential for interpreting results, understanding business context, and communicating findings, making their skills valuable alongside AI tools. Continuous learning in data visualization, programming, and machine learning remains important for the role.

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 infrastructure 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:
What are popular job titles related to Data Analytics Engineer jobs in Wisconsin? For Data Analytics Engineer jobs in Wisconsin, the most frequently searched job titles are:
What job categories do people searching Data Analytics Engineer jobs in Wisconsin look for? The top searched job categories for Data Analytics Engineer jobs in Wisconsin are:
Data Analytics Engineer jobs near you
Data & Analytics Engineer - Marketing Analytics

Data & Analytics Engineer - Marketing Analytics

Baird

Milwaukee, WI • On-site

Full-time

Posted 11 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 curious about how marketing data turns into insights that drive business decisions? Do you enjoy working hands-on with data while partnering closely with business stakeholders? Are you looking to deepen your skills in analytics engineering, data modeling, and modern data platforms?
As we continue to grow our data capabilities at Baird, we are seeking a Data & Analytics Engineer (DAE) with a focus on Marketing Analytics. This role is part of our IT Data & Analytics organization and supports marketing-focused use cases such as campaign performance, customer engagement, and channel analytics. The ideal candidate blends data engineering expertise with business curiosity, strong communication skills, and hands-on experience enabling analytics for Marketing stakeholders.
This role is based in Milwaukee, WI and works closely with Marketing, Analytics, Architecture, and Delivery teams.
The Impact You'll Make:
Marketing Analytics & Business Support
  • Partner with Marketing teams and analysts to support analytics needs related to campaigns, customer engagement, and performance reporting.
  • Help translate marketing questions into clear data requirements, datasets, and metrics.
  • Support analytics use cases such as campaign reporting, segmentation, funnel analysis, and customer insights.
  • Build familiarity and trust with Marketing Teams about marketing data sources and how they are used across the organization.

Data Engineering & Data Management
  • Contribute to the design, build, and maintenance of data pipelines that ingest and transform marketing 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 Marketing 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 with data engineering, analytics, or BI development.
  • Strong SQL skills and familiarity with relational data concepts.
  • Experience performing data analysis, profiling, and validation.
  • Ability to work with business partners to understand and support analytics needs.
  • Curiosity, strong problem-solving skills, and a desire to grow technically.

Technical Experience (Representative, Not Exhaustive)
  • Databases / Platforms: SQL Server, Snowflake, Azure SQL Database, Azure Data Lake.
  • Data Integration: SSIS, dbt, Azure Data Factory, or similar tools.
  • Query & Development: SQL, T-SQL, Azure Data Studio.
  • BI & Analytics Tools: Power BI, Alteryx, or similar.
  • Data Modeling & Governance: Basic 3NF and dimensional modeling, data mapping, data profiling, data quality concepts.
  • Data Formats: CSV, JSON, XML, Parquet.

Highly Preferred (Marketing Analytics)
  • Exposure to and experience with marketing or customer data (campaigns, digital engagement, CRM, or customer interaction data).
  • Interest in marketing measurement concepts such as attribution, segmentation, or funnels.
  • Experience working in a regulated or data-sensitive environment.

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