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Data Engineer Jobs in Kansas (NOW HIRING)

$98K - $118K/yr

The team works closely with product managers, backend engineers, web engineers, data scientists, analysts, business teams, and customer-facing teams to make data accurate, timely, scalable, and easy ...

Job Summary : Koch Engineered Solutions (KES) is currently looking for an Analytics Engineer to ... Responsibilities : • Partner with analysts and business stakeholders to understand data gaps ...

Data Center Operating Engineer Work Schedule : Friday Through Tuesday 3:30 pm to 11:30 pm with overtime and other assigned shifts as needed. We are a 24 /7 / 365 facility with 3 shifts of operation.

Job Title BI ETL Data Developer II or III Department Business Intelligence Team Worker Type Regular Pay Type Salary Position Salary Minimum 65,000 Position Salary Maximum 87,000 Salary will be ...

You'll work alongside a Staff Data Engineer (who owns the data foundation) and report to the Engineering Manager. Your focus is on the application and agentic AI layer: designing, building, and ...

Data Scientist - Process Modeling What you will do Let's do this. Let's change the world. In this ... Work closely with engineers to identify opportunities for process design improvements for Amgen ...

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Showing results 1-20

Data Engineer information

See Kansas salary details

$39.7K

$115.7K

$158.3K

How much do data engineer jobs pay per year?

As of Jul 14, 2026, the average yearly pay for data engineer in Kansas is $115,687.00, according to ZipRecruiter salary data. Most workers in this role earn between $102,100.00 and $122,600.00 per year, depending on experience, location, and employer.

Is a data engineer a difficult job?

A data engineer role involves designing, building, and maintaining data pipelines and infrastructure, which requires strong programming skills, knowledge of databases, and familiarity with tools like SQL, Python, and cloud platforms. The job can be challenging due to the complexity of managing large-scale data systems and ensuring data quality and security, but it is manageable with proper training and experience.

What is the difference between Data Engineer vs Data Scientist?

AspectData EngineerData Scientist
Primary FocusBuilding and maintaining data pipelines and infrastructureAnalyzing data to extract insights and create models
SkillsSQL, ETL, programming (Python, Java), database managementStatistics, machine learning, data analysis, programming (Python, R)
Work EnvironmentData warehouses, cloud platforms, backend systemsData analysis environments, research labs, visualization tools
Common ToolsApache Spark, Hadoop, Airflow, SQLJupyter, RStudio, Tableau, scikit-learn

Data Engineers focus on creating and maintaining the infrastructure that allows data to be collected, stored, and processed efficiently. Data Scientists analyze this data to generate insights, build predictive models, and support decision-making. While their skills overlap, Data Engineers are more involved in data pipeline development, whereas Data Scientists focus on data analysis and modeling.

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

To thrive as a Data Engineer, you need a strong background in computer science, data modeling, and programming languages such as Python or Java, often coupled with a relevant degree. Familiarity with ETL tools, big data frameworks (like Hadoop or Spark), and cloud platforms (such as AWS or Azure) is typically required, along with certifications like AWS Certified Data Analytics. Strong problem-solving skills, attention to detail, and effective communication set exceptional data engineers apart. These skills and qualities are essential for building robust data pipelines, ensuring data quality, and supporting data-driven decision-making across organizations.

What Does a Data Engineer Do?

The job duties of a data engineer involve helping with the development of systems, software, and infrastructure used to process, store and analyze data. Your responsibilities in this career include working to install data management software. Your employer may expect you to perform maintenance and install updates to all software and systems that they use for data acquisition, management, and analysis. Data engineers also analyze existing data systems to find ways to improve efficiency and accessibility. You then suggest upgrades or changes based on your assessment.

What are Data Engineers?

Data Engineers are IT professionals who design, construct, install, and maintain large-scale processing systems and other infrastructure for collecting, storing, and analyzing data. They build and optimize data pipelines and architectures that allow organizations to efficiently access and use data for business insights. Data Engineers work closely with data scientists, analysts, and other stakeholders to ensure that data is reliable, accessible, and secure. Their responsibilities often include working with databases, cloud platforms, and big data tools.

How do Data Engineers typically collaborate with Data Scientists and Analysts within an organization?

Data Engineers play a crucial role in ensuring that Data Scientists and Analysts have reliable, well-structured data for their projects. This collaboration often involves building and maintaining data pipelines, optimizing data storage solutions, and troubleshooting data quality issues. Regular communication and agile teamwork are common, with Data Engineers frequently participating in meetings to understand analytical requirements and adjust data processes accordingly. By working closely together, these teams can quickly iterate on data models and deliver actionable insights to drive business decisions.

What does a data engineer actually do?

A data engineer designs, builds, and maintains the infrastructure and pipelines that enable organizations to collect, store, and process large volumes of data. They work with tools like SQL, Python, and cloud platforms to ensure data is accessible, reliable, and ready for analysis by data scientists and analysts.

Is a data engineer entry level?

Data engineering is typically an intermediate to senior role that requires experience with programming, databases, and data pipelines. Entry-level positions may be available for those with relevant internships, certifications, or strong foundational skills in SQL, Python, or cloud platforms, but most roles expect prior experience or demonstrated technical competence.

What engineer makes $500,000 a year?

Senior data engineers with extensive experience, advanced skills in big data tools, and certifications can earn salaries approaching or exceeding $500,000 annually, especially in high-cost-of-living areas or within large tech companies. Such compensation often includes bonuses, stock options, and other incentives. These roles typically require strong programming, cloud platform expertise, and a deep understanding of data architecture.
What are the most commonly searched types of Data Engineer jobs in Kansas? The most popular types of Data Engineer jobs in Kansas are:
What are popular job titles related to Data Engineer jobs in Kansas? For Data Engineer jobs in Kansas, the most frequently searched job titles are:
What cities in Kansas are hiring for Data Engineer jobs? Cities in Kansas with the most Data Engineer job openings:
What are popular job titles related to Data Engineer jobs in KS? For Data Engineer jobs in KS, the most frequently searched job titles are:
Senior Data Architect

$63.75 - $85.50/hr

Full-time

Medical, Retirement, PTO

Posted 7 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

Booth IT: Application Development


About the Department

The University of Chicago Booth School of Business is the second-oldest business school in the U.S. and second to none when it comes to influencing business education and business practices. Since 1898, the school has produced ideas and leaders that shape the world of business. Their rigorous, discipline-based approach to business education transforms students into confident, effective, respected business leaders prepared to face the toughest challenges.
Chicago Booth has the finest set of facilities of any business school in the world. Each of the four campuses (two in Chicago, one in London, and one in Hong Kong) reflects the architectural traditions of its environs while offering a state-of-the-art learning environment.
Chicago Booth is proud to claim:
-an unmatched faculty.
-degree and open enrollment programs offered on three continents.
-a global body of nearly 56,000 accomplished alumni.
-strong and growing corporate relationships that provide a wealth of lifelong career opportunities.
As part of the world-renowned University of Chicago, Chicago Booth shares the University's core values that shape the distinctive intellectual culture. At Booth, they constantly question and test ideas, and seek proof. This extraordinarily effective approach to business leads to new ideas and innovative solutions. Seven of the Booth faculty members have won Nobel Prizes for these ideas - the first business school to achieve this accomplishment. For more information about the University of Chicago Booth School of Business, please visit: http://www.chicagobooth.edu/.


Job Summary

The Senior Data Architect is responsible for defining, governing, and leading the organization's enterprise data strategy, architecture roadmap, and cloud data modernization initiatives. This role serves as the enterprise authority for data architecture, data management, analytics platforms, and AI-ready data ecosystems, ensuring that organizational data assets are secure, trusted, accessible, and strategically aligned with business objectives. The Senior Data Architect provides technical and strategic leadership in the design, implementation, and optimization of scalable, secure, and high-performing cloud-based data solutions that support operational reporting, business intelligence, advanced analytics, artificial intelligence, and emerging data-driven initiatives. This position serves as the enterprise subject matter expert for Microsoft Fabric and the Microsoft Azure data ecosystem, leading the transition from legacy and on-premises data environments to modern cloud-native architectures.
This position collaborates closely with executive leadership, business stakeholders, Enterprise Architecture, Information Security, Application Development, Data Engineering, Analytics, and AI teams to establish enterprise standards, governance frameworks, and long-term data strategies that maximize the value of organizational data assets. The ideal candidate combines strategic vision, enterprise architecture expertise, strong leadership capabilities, and deep technical knowledge to drive innovation, operational excellence, and business value through data.

Responsibilities

  • Develops, maintains, and executes the enterprise data architecture strategy and multi-year roadmap aligned with organizational goals, digital transformation initiatives, and business priorities.
  • Leads the design, implementation, and optimization of enterprise cloud data platforms utilizing Microsoft Fabric, Azure Data Factory, Azure Data Lake Storage, Power BI, and related Azure technologies.
  • Architects scalable data warehouse, lakehouse, data mesh, and data integration solutions supporting enterprise reporting, analytics, and artificial intelligence initiatives.
  • Establishes and enforces enterprise standards, best practices, and governance policies for data architecture, data modeling, integration, metadata management, data lineage, security, and quality.
  • Leads enterprise data modernization and migration efforts from legacy and on-premises platforms to cloud-native architectures and services.
  • Designs and oversees enterprise ETL/ELT frameworks, data pipelines, orchestration processes, and DataOps practices to improve data delivery, reliability, and scalability.
  • Partners with executive leadership, business stakeholders, and technology teams to translate business requirements into scalable and sustainable enterprise data solutions.
  • Collaborates with Enterprise Architecture, Security Architecture, and Application Development teams to ensure alignment with organizational technology standards and strategic objectives.
  • Leads architecture reviews and provides governance oversight for enterprise data solutions, ensuring compliance with approved standards and architectural principles.
  • Provides technical leadership, mentorship, and architectural guidance to data engineers, developers, analysts, AI engineers, and project teams.
  • Evaluates emerging technologies and industry trends, recommending innovative solutions that enhance organizational data capabilities, AI readiness, performance, and cost efficiency.
  • Develops and promotes data-as-a-product principles to improve accessibility, usability, and business adoption of enterprise data assets.
  • Establishes cloud cost optimization and FinOps strategies to balance performance, scalability, and operational expenditures.
  • Ensures compliance with data governance, privacy, security, regulatory, and institutional requirements while fostering a culture of data stewardship and accountability across the organization.
  • Manages a team of developers, assign work, coach and mentor.
  • Acts as a technical consultant and resource for faculty research, teaching, and/or administrative projects.
  • Leads or coordinates teams or projects for activities relating to software support and/or development.
  • 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 7+ years of work experience in a related job discipline.


Certifications:

---

Preferred Qualifications

Education:

  • Master's degree.

Experience:

  • Minimum twelve years of progressively responsible experience in enterprise data architecture, data engineering, data warehousing, enterprise data management, analytics platforms, and cloud data solutions.

Certifications:

  • Microsoft Certified Fabric Data Engineer.

Technical Skills or Knowledge:

  • Proficient in designing, implementing, and leading enterprise cloud data platforms and modernization initiatives with Microsoft Azure environments.
  • Expert-level knowledge of Microsoft Fabric, Azure Data Factory, Azure Synapse Analytics, Azure Data Lake Storage, Power BI, OneLake, and related Azure data services.
  • Accomplished in enterprise data modeling methodologies including conceptual, logical, physical, dimensional, semantic, and canonical data models.
  • Strong proficiency in SQL, Python, Spark, ETL/ELT development, data engineering, DataOps, and cloud-native data architecture practices.
  • Proficient with enterprise integration architectures utilizing APIs, event-driven architectures, streaming technologies, and cloud-native integration services.
  • Familiar with enterprise data quality frameworks, validation methodologies, testing strategies, reconciliation processes, and data observability practices.
  • Demonstrated experience leading enterprise-scale cloud migration, modernization, and digital transformation initiatives.
  • Deep understanding of data, metadata management, data lineage, data quality, security, privacy, and compliance frameworks.
  • Seasoned professional at implementing and supporting artificial intelligence, advanced analytics, and generative AI platforms through scalable data architecture design.
  • Proficient in Azure DevOps, GitHub, CI/CD pipelines, and modern software delivery practices.
  • Strong understanding of cloud cost management, FinOps principles, performance optimization, and operational excellence.

Preferred Competencies

  • Proven ability to influence executive stakeholders, communicate architectural strategies, and lead cross-functional initiatives across business and technology organizations.
  • Excellent leadership, communication, stakeholder management, problem-solving, and strategic planning skills with the ability to communicate effectively at both technical and executive levels.

Working Conditions

  • This position is currently expected to work a minimum three days per week in the office.

Application Documents

  • Resume/CV (required)
  • Cover Letter (required)


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

Information Technology


Role Impact

Individual Contributor


Scheduled Weekly Hours

37.5


Drug Test Required

No


Health Screen Required

No


Motor Vehicle Record Inquiry Required

No


Pay Rate Type

Salary


FLSA Status

Exempt


Pay Range

$155,000.00 - $175,000.00

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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