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Python Data Jobs in Wisconsin (NOW HIRING)

Vultus Inc

Data Engineer

Seymour, WI · On-site

$116K - $140K/yr

The ideal candidate should have strong experience in SQL, Python, ETL/ELT processes, cloud data platforms, and data warehousing. Key Responsibilities * Design, develop, and maintain reliable data ...

Dentsu Aegis Network Ltd.

WI · On-site

$136 - $190/hr

Architect, develop, and test production grade Python APIs for media products. Orchestration ... Support data pipelines, background jobs, and distributed systems that interact with AI models.

Arbeidsplassen

WI · On-site

$100 - $125/hr

Join as a Data Engineer in our Data Product Engineering team within Schibsted's Data & AI ... Our everyday toolkit includes SQL and Python as core languages, together with Snowflake, dbt ...

Variyasinc

WI · On-site

$100 - $125/hr

* Build and maintain data pipelines for machine learning models ... Develop Python code to run feature preprocessing and feature engineering on large Datasets.

Innovizant LLC

Data Scientist

Madison, WI · On-site

Qualifications Data Science, Analysis, Python, R, Statistical Modeling, Machine Learning Additional Information Thanks & Regards, Aditya Prakash / Resource Manager / Innovizant LLC Phone : 630-685 ...

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Python Data information

What is a Python Data professional?

A Python Data professional is someone who uses the Python programming language to analyze, process, and interpret data. They work with large datasets, perform data cleaning and transformation, and apply statistical or machine learning techniques to extract insights. These professionals often work in roles such as data analyst, data scientist, or data engineer, and use Python libraries like Pandas, NumPy, and scikit-learn to accomplish their tasks.

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

To thrive as a Python Data professional, you need strong programming skills in Python, a solid understanding of data structures, algorithms, and experience with data analysis or data science, typically supported by a relevant degree. Familiarity with technical tools such as pandas, NumPy, SQL, Jupyter Notebooks, and often cloud platforms or machine learning frameworks is important, and certifications like Microsoft or Google Data certifications can be advantageous. Strong analytical thinking, attention to detail, and effective communication help you extract insights from data and collaborate with stakeholders. These skills and qualities are essential to efficiently process, analyze, and interpret data, driving informed business decisions.

What are some common challenges faced by Python Data professionals when working with large datasets?

Python Data professionals often encounter challenges such as optimizing code to handle large volumes of data efficiently and managing memory usage to prevent slowdowns or crashes. Working with big datasets may require leveraging tools like pandas, NumPy, or Dask, and sometimes integrating with distributed computing systems such as Apache Spark. Additionally, ensuring data quality and managing data pipelines for consistent and accurate results can be demanding. Collaborating closely with data engineers, analysts, and other stakeholders is common to ensure smooth data flow and analysis.

What is the difference between Python Data vs Data Analyst?

AspectPython DataData Analyst
Required SkillsPython programming, data manipulation, scriptingExcel, SQL, data visualization
CertificationsPython certifications, data science coursesData analysis certifications, Excel certifications
Work EnvironmentData science teams, programming-heavy rolesBusiness intelligence, reporting teams
Industry UsageTech, finance, healthcareRetail, marketing, finance

Python Data roles focus on programming, data manipulation, and building data pipelines using Python, while Data Analysts primarily analyze data using tools like Excel and SQL to generate reports and insights. Both roles often collaborate but differ in technical depth and tools used.

Are Python coders in demand?

Python developers are in high demand across various industries due to the language's versatility in data analysis, web development, and automation. Employers seek skills in frameworks like Django and data tools such as Pandas, making Python a valuable programming language for job seekers. The demand is expected to grow as data-driven decision-making and automation increase in the workplace.

How much do Python data scientists make?

Python data scientists typically earn a median salary ranging from $90,000 to $130,000 annually, depending on experience, location, and industry. Advanced skills in machine learning, data analysis, and proficiency with tools like Pandas and TensorFlow can lead to higher compensation.

Is Python Data still in demand in 2026?

Python data roles remain in high demand in 2026 due to the language's widespread use in data analysis, machine learning, and automation. Skills in libraries like Pandas, NumPy, and frameworks such as TensorFlow enhance job prospects, and proficiency in data management tools is often required.

What are popular job titles related to Python Data jobs in Wisconsin?

For Python Data jobs in Wisconsin, the most frequently searched job titles are:

What job categories do people searching Python Data jobs in Wisconsin look for?

The top searched job categories for Python Data jobs in Wisconsin are:

Python Data jobs near you
Infographic showing various Python Data job openings in Wisconsin as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution.

Data Engineer

Seymour, WI • On-site

Vultus Inc
Software Development • 11 - 50 employees
Learn more about Vultus Incexternal

$116K - $140K/yr

Full-time

Posted 15 days ago

Job description

Data Engineer

Experience

2–5 years

Job Type

Full-time

Job Summary

We are looking for a skilled Data Engineer to design, develop, and maintain scalable data pipelines and data processing solutions. The ideal candidate should have strong experience in SQL, Python, ETL/ELT processes, cloud data platforms, and data warehousing.

Key Responsibilities
  • Design, develop, and maintain reliable data pipelines for batch and real-time data processing.
  • Build and optimize ETL/ELT workflows from multiple data sources.
  • Develop complex SQL queries, stored procedures, and data transformations.
  • Work with data warehouses, data lakes, and cloud-based data platforms.
  • Perform data cleansing, transformation, validation, and integration.
  • Monitor data pipelines and troubleshoot failures, performance issues, and data-quality problems.
  • Optimize data processing jobs and database queries for performance and scalability.
  • Implement data-quality checks and ensure data accuracy and consistency.
  • Collaborate with Data Scientists, BI Developers, Analysts, and Software Engineers.
  • Participate in data architecture and pipeline design discussions.
  • Maintain technical documentation for data pipelines, workflows, and data models.
  • Follow security, governance, and best practices for handling enterprise data.
Required Skills
  • Strong proficiency in SQL.
  • Strong programming experience in Python.
  • Hands-on experience with ETL/ELT pipelines.
  • Experience with data warehousing concepts and dimensional data modeling.
  • Experience with databases such as SQL Server, PostgreSQL, MySQL, or similar.
  • Experience working with cloud platforms such as Microsoft Azure, AWS, or GCP.
  • Understanding of data lakes and distributed data processing.
  • Experience with version control systems such as Git.
  • Strong understanding of data quality, data validation, and error handling.
Preferred Skills
  • Experience with Microsoft Fabric, Azure Data Factory, Azure Synapse, or Databricks.
  • Experience with Apache Spark/PySpark.
  • Knowledge of Power BI and BI data models.
  • Experience with streaming technologies such as Kafka.
  • Knowledge of CI/CD and DevOps practices.
  • Experience working with REST APIs and integrating data from external systems.
  • Familiarity with data governance, security, and compliance.
Education
  • Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
Soft Skills
  • Strong analytical and problem-solving skills.
  • Good communication and collaboration skills.
  • Ability to work independently and as part of a team.
  • Strong attention to detail.
  • Ability to troubleshoot complex data issues.
Key Qualifications
  • 2–5 years of hands-on experience in Data Engineering.
  • Strong SQL and Python expertise.
  • Practical experience developing and supporting production data pipelines.
  • Good understanding of cloud data engineering and modern data architecture.