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Software Engineer Data Analyst Jobs in Wisconsin

Winaxis

Software Engineer

Pleasant Prairie, WI · On-site

... Data). - Build and deploy production-grade microservices on Kubernetes, with a focus on ... object-oriented software analysis and design, following industry best practices and patterns ...

Bankers' Bank

Data Analyst - WI

Madison, WI · On-site

Data Analysis (40%) * Conduct exploratory data analysis to identify trends, patterns, and ... Basic knowledge of programming languages (i.e., Python) and querying languages (i.e., SQL)

Bankers' Bank

Data Analyst - WI

Madison, WI · On-site

Data Analysis (40%) * Conduct exploratory data analysis to identify trends, patterns, and ... Basic knowledge of programming languages (i.e., Python) and querying languages (i.e., SQL)

Husch Blackwell Llp

Enterprise Data Analyst

Madison, WI · On-site +1

Partner with the Data Engineering team to source, integrate, and validate data from across the Firm ... Connect analytical findings to business outcomes and Firm priorities Continuous Improvement ...

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Showing results 21-40

All JobsSoftware Engineer Data Analyst JobsSoftware Engineer Data Analyst Jobs in Wisconsin

Software Engineer Data Analyst information

See Wisconsin salary details

$44.9K

$130.9K

$179.2K

How much do software engineer data analyst jobs pay per year?

As of Sep 2, 2026, the average yearly pay for software engineer data analyst 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.

What is a software engineer data analyst?

A Software Engineer Data Analyst is a professional who combines software engineering skills with data analysis expertise to extract insights from data and build applications or tools for data processing. They typically design, develop, and maintain software systems that collect, store, and analyze large datasets. Their role often involves writing code to automate data workflows, create dashboards, and perform statistical analyses. These professionals work closely with other engineers, data scientists, and business stakeholders to support data-driven decision making.

How do software engineer data analysts typically collaborate with other teams to deliver data-driven solutions?

Software Engineer Data Analysts work closely with cross-functional teams, including data scientists, product managers, and software developers, to collect requirements and translate business needs into actionable analytics solutions. They often participate in regular meetings to align on project goals, share progress, and troubleshoot data integration challenges. Effective communication is key, as they must explain technical findings to non-technical stakeholders and ensure that the data pipelines and dashboards they develop meet end-user needs. This collaborative environment provides opportunities to broaden technical skills and gain insights into various business functions.

What are the key skills and qualifications needed to thrive as a software engineer data analyst, and why are they important?

To thrive as a Software Engineer Data Analyst, you need strong programming skills (such as Python or Java), a solid understanding of data structures and algorithms, and a background in statistics or computer science. Proficiency in SQL, data visualization tools (like Tableau or Power BI), and experience with big data platforms (such as Hadoop or Spark) are typically required, along with relevant certifications. Analytical thinking, problem-solving ability, and effective communication help you translate complex data into actionable insights. These skills ensure you can extract, analyze, and communicate data-driven solutions that support business objectives.

What is the difference between Software Engineer Data Analyst vs Data Scientist?

AspectSoftware Engineer Data AnalystData Scientist
Required CredentialsBachelor's in CS, Data Analysis, or related; programming skillsBachelor's or higher in CS, Statistics, or related; advanced analytics skills
Work EnvironmentSoftware development teams, data analysis projectsResearch, modeling, predictive analytics teams
Employer & Industry UsageTech companies, finance, healthcareTech firms, research institutions, finance
Common Search & ComparisonOften compared for data roles involving coding and analysisMore focused on predictive modeling and research

The main difference between a Software Engineer Data Analyst and a Data Scientist lies in their focus and skill set. Software Engineers Data Analysts primarily develop data tools and analyze data using programming, while Data Scientists focus on building predictive models and advanced analytics. Both roles require strong technical skills, but Data Scientists typically have more expertise in statistics and machine learning.

What cities in Wisconsin are hiring for Software Engineer Data Analyst jobs?

Cities in Wisconsin with the most Software Engineer Data Analyst job openings:

Software Engineer Data Analyst jobs near you

Data Platform Engineer

Purplejack Technologies LLC

Brownsville, WI • On-site

$125K - $150K/yr

Other

Posted 8 days ago

Job description

Hello,
Hope you are doing well.
I came across your resume on a job portal, and your background appears to be a strong match for an exciting opportunity we are currently hiring for.
Position:  IT Manager - Data Platform & Engineering
Location:   Brownsville, WI
Fulltime.
Must-Have Skills

  • Bachelor''s degree in Computer Science, Information Systems, Engineering, or a related quantitative or technical field, or equivalent hands-on experience
  • 8+ years of experience in data engineering, data platform engineering, or software engineering
  • 4+ years leading technical teams with accountability for hiring, coaching, and delivery
  • Proven experience building and operating large-scale, complex cloud data platforms such as Databricks, Snowflake, Microsoft Fabric, or BigQuery
  • Experience delivering governed, reusable data products serving·      
  • Experience delivering governed, reusable data products serving organizations across multiple departments and technical personas
  • Deep hands-on proficiency with SQL, Python, and modern data engineering practices, including orchestration, transformation, automated testing, CI/CD, and both batch and streaming Ingestion.
  •  Experience building reliable, observable pipelines with monitoring, lineage, and data quality controls that operate within enterprise governance, privacy, and security requirements
  • Track record of building AI-ready data platforms that are well-documented, well-structured, and trustworthy enough to serve both analytics and AI/GenAI use cases

 
Key Responsibilities 
  •  Recruit, hire, and develop the founding data engineering team, establishing the roles, standards, and operating practices needed to scale responsibly. 
  • Lead the buildout of the enterprise data platform on the selected technology stack, implementing ingestion, storage, transformation, and orchestration layers that convert raw source data into trusted, reusable assets. 
  • Partner with business and technology stakeholders to understand their needs and sequence the engineering backlog, making deliberate tradeoffs across value, speed, cost, risk, and maintainability. 
  • Stay hands-on as a technical leader, working alongside the team to design, build, and optimize the pipelines and transformation logic behind priority data products. 
  • Collaborate with data architecture and data governance teams to ensure platform decisions are durable, interoperable, and ready to support future analytics and AI use cases.  Establish foundational engineering disciplines that enable a lean team to reliably operate and support what it builds, using AI and automation to extend capacity.


Description
The IT Manager of Data Platform & Engineering leads the development and evolution of an enterprise data platform. As a founding leader on the Enterprise Intelligence team, this individual will build and lead the data engineering function, establish engineering best practices, and deliver trusted, governed data products. This role partners across business and IT teams to enable analytics, reporting, operational insights, and AI while creating a scalable data foundation for the future. 
--
Regards,
Pooja Shikha
+1-

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