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Data Visualization Engineer Jobs in Chicago, IL (NOW HIRING)

Relevant Work Experience * 5+years of experience in software engineering, with a focus on data ... Experiencewith Power BI/Tableaufor reporting and data visualization. * Excellent problem-solving ...

Relevant Work Experience * 5+years of experience in software engineering, with a focus on data ... Experiencewith Power BI/Tableaufor reporting and data visualization. * Excellent problem-solving ...

Perform feature engineering to enhance data models for machine learning applications. * Collaborate ... Knowledge of data visualization tools such as Tableau or Matplotlib. * Prior experience with big ...

Sr. Azure Data Engineer

Northbrook, IL · On-site

$101K - $152K/yr

Relevant Work Experience * 5+ years of experience in software engineering, with a focus on data ... Experience with Power BI / Tableau for reporting and data visualization. * Excellent problem ...

... data visualization best practices and accessibility standards across reporting solutions • ... programming interfaces (APIs) • Strong background in data visualization best practices and ...

Analyze operational data using data visualization tools (Tableau, Power BI) to identify trends ... Engineering background in Mining Engineering, Metallurgy, or a related discipline . * Experience in ...

Strong proficiency in Python, R, SQL, or similar programming languages * Advanced experience with Tableau, Power BI, or data visualization tools * Experience with predictive modeling, machine ...

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Data Visualization Engineer information

See Chicago, IL salary details

$45.8K

$133.6K

$182.8K

How much do data visualization engineer jobs pay per year?

As of Jul 14, 2026, the average yearly pay for data visualization engineer in Chicago, IL is $133,597.00, according to ZipRecruiter salary data. Most workers in this role earn between $117,900.00 and $141,600.00 per year, depending on experience, location, and employer.

What is a Data Visualization Engineer job?

A Data Visualization Engineer is responsible for designing, developing, and implementing visual representations of data to help stakeholders understand complex information. They use tools like Tableau, D3.js, Power BI, and Python libraries (e.g., Matplotlib, Seaborn) to create interactive dashboards and reports. Their role involves working with large datasets, ensuring data accuracy, optimizing performance, and collaborating with analysts and developers to enhance decision-making. Strong programming, data analysis, and UX/UI design skills are essential for success in this role.

What are some common challenges faced by Data Visualization Engineers, and how can they overcome them?

Data Visualization Engineers often encounter challenges such as translating complex data into clear, actionable visuals for non-technical stakeholders and ensuring that graphics remain both accurate and engaging. Balancing the needs of different departments, adhering to fluctuating project requirements, and managing large or messy datasets can also be demanding. Successful engineers address these issues by working closely with data analysts, business users, and designers, using feedback to iterate on their work, and staying current with the latest visualization best practices. Proactive communication and strong organization skills further help in meeting deadlines and maintaining quality standards.

What are the key skills and qualifications needed to thrive in the Data Visualization Engineer position, and why are they important?

To thrive as a Data Visualization Engineer, you need a strong grasp of data analysis, visual storytelling, and programming, often supported by a degree in computer science, data science, or a related field. Familiarity with tools like Tableau, Power BI, D3.js, and proficiency in languages such as Python or JavaScript are commonly required, along with experience in databases and dashboard development. Strong communication, problem-solving, and collaboration skills help you effectively transform and present complex data to diverse audiences. These abilities are crucial for creating impactful, user-friendly visualizations that drive informed business decisions.

What are the most commonly searched types of Data Visualization Engineer jobs in Chicago, IL? The most popular types of Data Visualization Engineer jobs in Chicago, IL are:
What are popular job titles related to Data Visualization Engineer jobs in Chicago, IL? For Data Visualization Engineer jobs in Chicago, IL, the most frequently searched job titles are:
What job categories do people searching Data Visualization Engineer jobs in Chicago, IL look for? The top searched job categories for Data Visualization Engineer jobs in Chicago, IL are:
Infographic showing various Data Visualization Engineer job openings in Chicago, IL as of July 2026, with employment types broken down into 1% As Needed, 84% Full Time, 13% Part Time, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $133,597 per year, or $64.2 per hour.
Staff Data Scientist & AI Researcher

Staff Data Scientist & AI Researcher

University of Chicago Library

Chicago, IL

Full-time

Medical, Retirement, PTO

Posted 3 days ago


University Of Chicago rating

8.1

Company rating: 8.1 out of 10

Based on 47 frontline employees who took The Breakroom Quiz

134th of 553 rated colleges and universities


Job description

Department

BSD CTD - Data Science


About the Department

The Center for Translational Data Science (CTDS) at the University of Chicago is a research center whose mission is to develop the discipline of translational data science to impactful problems in biology, medicine, healthcare, and the environment. We envision a world in which researchers have ready access to the data needed and the tools required to make data driven discoveries that increase our scientific knowledge and improve the quality of life. We architect ecosystems of large-scale commons of research data, computing resources, applications, tools, and services for the broader research community to use data at scale to pursue scientific inquiry and accelerate discovery. Learn more at https://gdc.cancer.gov/ https://gen3.org/ https://stats.gen3.org/ and https://ctds.uchicago.edu/.


Job Summary

The Center for Translational Data Science at the University of Chicago is seeking a Staff Data Scientist to support a diverse range of research projects. Data Scientists work in a collaborative interdisciplinary team and play a critical role in AI/ML tooling, features, and improvements for our open-source software systems and applications, analyzing data, and in understanding and representing user requirements to internal and external stakeholders in our translational data science projects and products. Under the leadership of team or project leads, a person in this position will be a key contributor to the design and implementation of algorithms, AI/ML models, and workflows to enable the discovery of valuable information in large volumes of data from various sources; organizes, harmonizes, and analyzes data sets and develops tools to assist such processes; uses various technologies to visualize data or enable data visualization; and creates applications of general value to the project and product owners. The job uses best practices and advanced knowledge of data manipulation, statistical applications, programming, analysis and modeling in order to implement projects related to the University's various internal data systems as well as from external sources.
This at-will position is wholly or partially funded by contractual grant funding which is renewed under provisions set by the grantor of the contract. Employment will be contingent upon the continued receipt of these grant funds and satisfactory job performance.

Responsibilities

  • Leading the Interpretation of data from multiple sources.

  • Developing and implementing software programs and services, software notebooks and software scripts for data transformation, data integration, data analysis and data visualization.

  • Building, validating and evaluating AI/ML models.

  • Contributing to and taking a leadership role in the enhancement and maintenance of previously developed in-house open-source data platforms, systems, applications and notebooks.

  • Performing various types of analysis involving multiple data sets.

  • Leading data science projects and initiatives within purview, by relaying data analysis and model deployment best practices, enhancing the technical knowledge of peers, and helping develop data science skills in junior employees and interns.

  • Leading the conceptualization, design, and execution of sophisticated data science projects and AI/ML solutions for research and production environments.

  • Establish and enforce data governance, quality assurance processes, and operational protocols for large, complex data sets from internal and external sources.

  • Assisting in providing leadership for design of user-facing computational resources.

  • Serving as a reference for staff, faculty members, and Gen3 users as a technical subject matter expert by applying principles of data science to define and scope data science projects that involve developing computational tools and services for data engineering, data manipulation, statistical analysis, and modeling.

  • Collaborating closely with faculty, researchers, and stakeholders to translate scientific and user requirements into actionable data science strategies and solutions.

  • Stay current with developments in data science, machine learning, artificial intelligence, and related fields, and adopt new methods and technologies to advance research goals.

  • Communicate complex technical concepts and project results clearly to technical and non-technical audiences, and present findings at internal and external forums.

  • Has a deep understanding of methods to analyze complex data sets for the purpose of extracting and purposefully using applicable information. May develop and maintain infrastructure that connects data sets.

  • Guides staff or faculty members in defining the project and applies principals of data science in manipulation, statistical applications, programming, analysis and modeling.

  • Calibrates data between large and complex research and administrative datasets. Guides and may set the operational protocols for collecting and analyzing information from the University's various internal data systems as well as from external sources.

  • Performs other related work as needed.


Minimum Qualifications

Education:

Minimum requirements include a college or university degree in related field.


Work Experience:

Minimum requirements include knowledge and skills developed through 5-7 years of work experience in a related job discipline.


Certifications:

---

Preferred Qualifications

Education:

  • Advanced degree in Computer Science, Data Science, Statistics, Mathematics, Bioinformatics, or a relevant quantitative field.

Experience:

  • Experience working in data science roles, preferably in an academic, research, or health/science environment.

  • Experience with collaborative open-source projects and software engineering best practices.

  • Experience working in multi-disciplinary academic teams.

  • Knowledge of biomedical and translational research data sources is a significant advantage.

  • Knowledge of hardware specifications required for AI/ML research and projecting resource needs and use in public clouds environments like AWS and GCP.

  • Knowledge of and experience with data and applications of interest to CTDS, including, but not necessarily limited to, AI data commons, AI data meshes, Gen3, NCI Genomic Data Commons, cancer genomics, biomedical imaging data, human clinical data.

  • Expertise in designing and implementing machine learning, deep learning, and statistical models for research and production.

  • Experience with biomedical data.

  • Experience collaborating on manuscripts and submitting papers for peer-reviewed, scientific publications.

Preferred Competencies

  • Advanced skills in problem solving and quantitative/qualitative analysis.

  • Able to organize and prioritize work assignments to meet project needs and work independently to identify and address needs beyond assigned tasks.

  • Strong communication skills to effectively convey complex findings while serving as a reference and subject matter expert for staff, faculty members, and Gen3 users.

  • Ability to quickly comprehend requirements and assignments and then explain his/her solutions in both writing and speech.

  • Ability to learn new skills quickly and manage complex projects.

  • Proficiency in Python, R, and other relevant programming languages; experience with open-source data science platforms, technologies, and cloud environments.

  • Outstanding analytical, problem-solving, and project management abilities.

  • Proven track record mentoring and leading project teams and communicating technical issues to diverse audiences.

  • Excellent written and verbal communication skills.

Working Conditions

  • Hybrid office/remote.

Application Documents

  • Resume/CV (required)

  • Cover Letter (preferred)


The University of Chicago uses AI-assisted tools to streamline and augment some recruitment processes; however, AI is not used to make hiring decisions.
When applying, the document(s) MUSTbe uploaded via the My Experience page, in the section titled Application Documents of the application.


Job Family

Research


Role Impact

Individual Contributor


Scheduled Weekly Hours

40


Drug Test Required

No


Health Screen Required

No


Motor Vehicle Record Inquiry Required

No


Pay Rate Type

Salary


FLSA Status

Exempt


Pay Range

$90,000.00 - $120,000.00

The included pay rate or range represents the University's good faith estimate of the possible compensation offer for this role at the time of posting.


Benefits Eligible

Yes

The University of Chicago offers a wide range of benefits programs and resources for eligible employees, including health, retirement, and paid time off. Information about the benefit offerings can be found in the Benefits Guidebook.


Posting Statement

The University of Chicago is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, sexual orientation, gender, gender identity, or expression, national or ethnic origin, shared ancestry, age, status as an individual with a disability, military or veteran status, genetic information, or other protected classes under the law. For additional information please see the University's Notice of Nondiscrimination.

Job seekers in need of a reasonable accommodation to complete the application process should call 773-702-5800 or submit a request via Applicant Inquiry Form.

All offers of employment are contingent upon a background check that includes a review of conviction history. A conviction does not automatically preclude University employment. Rather, the University considers conviction information on a case-by-case basis and assesses the nature of the offense, the circumstances surrounding it, the proximity in time of the conviction, and its relevance to the position.

The University of Chicago's Annual Security & Fire Safety Report (Report) provides information about University offices and programs that provide safety support, crime and fire statistics, emergency response and communications plans, and other policies and information. The Report can be accessed online at:http://securityreport.uchicago.edu.Paper copies of the Report are available, upon request, from the University of Chicago Police Department, 850 E. 61st Street, Chicago, IL 60637.


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