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Data Engineer Jobs in Springfield, IL (NOW HIRING)

Provide field testing to determine appropriate capabilities in situations not covered by test data * Review project specifications or calculations for engineers and architects; provide feedback to ...

Description & Requirements Maximus is searching for a Data Coordination Analyst role supporting upcoming federal OPTN work, contingent upon contract award. In this role, you will transform complex ...

Geotechnical Engineer

Springfield, IL · On-site

$85K - $120K/yr

... data reduction. * Prepare geotechnical reports, foundation recommendations, slope stability ... Bachelor's degree in civil engineering or related field. * Minimum of 4 years of experience in ...

From design to engineering and permitting assistance, no other privately-held engineering firm ... Analyze technical data * Report writing Implement logic and creativity in Design Issues * Effective ...

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Data Engineer information

See Springfield, IL salary details

$44.1K

$128.6K

$175.9K

How much do data engineer jobs pay per year?

As of Jul 14, 2026, the average yearly pay for data engineer in Springfield, IL is $128,563.00, according to ZipRecruiter salary data. Most workers in this role earn between $113,500.00 and $136,300.00 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 Springfield, IL? The most popular types of Data Engineer jobs in Springfield, IL are:
What are popular job titles related to Data Engineer jobs in Springfield, IL? For Data Engineer jobs in Springfield, IL, the most frequently searched job titles are:
What job categories do people searching Data Engineer jobs in Springfield, IL look for? The top searched job categories for Data Engineer jobs in Springfield, IL are:
What cities near Springfield, IL are hiring for Data Engineer jobs? Cities near Springfield, IL with the most Data Engineer job openings:

Lead Data Scientist (Artificial Intelligence/Machine Learning)

Criminal Investigation & Law Enforcement | IRS Careers

Springfield, IL

$125K/yr

Other

Posted 13 days ago


Job description

WHAT IS INFORMATION TECHNOLOGY ?
A description of the business units can be found at: https://www.jobs.irs.gov/about/who/business-divisions
  • Position(s) are to be filled in following area(s):
    • IT - Taxpayer Services and Online Accounts
  • Consider each location carefully when applying. If you are selected for a location, that location will become your official post of duty.
REVIEW THE ADDITIONAL INFORMATION BELOW FOR FURTHER DETAILSQualifications:

Federal experience is not required. Experience may have been gained in the public sector, private sector or through Volunteer Service. One year of experience refers to full-time work; part-timework is considered on a prorated basis. To ensure full credit for your work experience, please indicate dates of employment by month/day/year, and indicate number of hours worked per week, on your resume.
You must meet the following requirements by the closing date of this announcement.
BASIC REQUIREMENTS All GRADES: EDUCATION:
You must have a bachelor's or higher degree in mathematics, statistics, computer science, data science or other field directly related to the position. The degree must be in a major field of study (at least at the baccalaureate level) that is appropriate for the position.
OR
COMBINATION OF EDUCATION AND EXPERIENCE: A combination of education and experience that includes courses equivalent to a major field of study (30 semester hours) as shown in the paragraph above, plus additional education or appropriate experience.
SPECIALIZED EXPERIENCE GRADE 14: In addition to the basic requirements, you must have one (1) year of specialized experience at a level of difficulty and responsibility equivalent to the GS-13 grade level in the Federal service. Specialized experience for this position includes:

  • Designing, developing, integrating, testing, and supporting conversational AI solutions, virtual assistants, chatbots, digital messaging platforms, voice automation, interactive voice response (IVR) platforms, or generative AI-enabled customer engagement solutions in a production environment.
  • Developing and optimizing natural language understanding (NLU), natural language processing (NLP), speech recognition, intent classification, entity recognition, conversational workflows, or automated self-service solutions supporting customer interactions across voice and digital channels.
  • Designing, testing, implementing, and refining prompt engineering strategies, generative AI workflows, large language model (LLM) integrations, and AI-assisted customer engagement capabilities to improve automation, containment, customer experience, and operational outcomes.
  • Integrating conversational AI, generative AI, voice, chat, messaging, or digital engagement platforms with enterprise applications, APIs, backend systems, authentication services, customer data platforms, or knowledge management solutions.
  • Demonstrating subject matter expert (SME)-level proficiency in at least one modern programming language such as Java or Python, including development of backend services, automation, integrations, data processing pipelines, or conversational application logic.
  • Analyzing customer interaction data, conversation transcripts, chat sessions, operational metrics, and user behavior to identify trends, improve AI performance, evaluate model effectiveness, and enhance customer experience outcomes.
  • Developing, querying, and analyzing large datasets using cloud-based analytics platforms and data warehouses to support AI model evaluation, operational reporting, and business decision-making.
  • Troubleshooting and resolving complex system integration, application reliability, authentication, speech processing, conversational AI, generative AI, digital engagement, or performance issues across interconnected platforms.
  • Applying DevSecOps, CI/CD pipelines, automated testing, version control, and agile software development practices in enterprise environments.
  • Collaborating with business stakeholders, architects, engineers, cybersecurity personnel, data scientists, and operations teams to translate business requirements into AI-enabled technical solutions.

AND
You must also meet the following requirement(s):

  • PERFORMANCE RATING: Current federal employees must have at least a fully successful or equivalent performance rating to receive consideration.
  • TIME AFTER COMPETITIVE APPOINTMENT (TACA): By the closing date (or if this is an open continuous announcement, by the cut-off date) specified in this job announcement, current civilian employees must have completed at least 90 days of federal civilian service since their latest non-temporary appointment from a competitive referral certificate, known as time after competitive appointment. For this requirement, a competitive appointment is one where you applied to and were appointed from an announcement open to "All US Citizens"
  • TIME IN GRADE (TIG): Federal employees must meet time-in-grade requirements. For positions above the GS-05,applicants must meet applicable time-in-grade requirements to be considered eligible. One year (52 weeks) at the next lower grade level is required to meet the time-in-grade requirements for the grade you are applying for. For positions at the GS-05, you cannot advance to the GS-05 if you have held a GS-02 in the past 52 weeks. There is no TIG restriction for GS-02, 03, or 04 positions.


For more information on qualifications please refer to OPM's Qualifications Standards.

Education:A college or university degree generally must be from an accredited (or pre-accredited) college or university recognized by the U.S. Department of Education. For a list of schools which meet these criteria, please refer to Department of Education Accreditation page.
FOREIGN EDUCATION: Education completed in foreign colleges or universities may be used to meet the requirements. You must show proof the education credentials have been deemed to be at least equivalent to that gained in conventional U.S. education program. It is your responsibility to provide such evidence when applying. Click here (Section 3, Explanation of Terms) or here for Foreign Education Credentialing instructions.
We recommend choosing an evaluator from a member organization of one of the following national associations of credential evaluation services: National Association of Credential Evaluation Services (NACES) or Association of International Credentials Evaluators (AICE).Employment Type: OTHER