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Data Engineer Jobs in Bloomington, IL (NOW HIRING)

1 point system

Senior Data Engineer

Normal, IL · On-site

$103K - $140K/yr

As a Sr. Data Engineer, you will help build and operate the data foundation that powers analytics across programs and sites. You will design and maintain scalable ingestion pipelines, develop well ...

Kemper

Senior Data Systems Analyst

Bloomington, IL

The Data Systems Analyst serves as an independent quality function within the Data Engineering ... Partner with engineering and operational teams to prioritize remediation activities. * Track ...

Kemper

Data Science Manager

Bloomington, IL · Hybrid

Manages a small team of data scientists and data engineers to research, design, develop, deploy, and maintain machine learning, AI, and agentic AI solutions supporting the Claims organization.

Caterpillar

Data Scientist

Morton, IL · On-site

This role requires strong programming skills, the ability to learn complex business processes, and a data-driven mindset. While initially focused on this high-impact software modernization effort ...

Codvo.ai

Data Scientist (Dallas)

Texas, IL

We believe in a culture of innovation, collaboration, and growth, where engineers can experiment, learn, and thrive. Join us to be part of a team that solves complex data challenges with creativity ...

Munich Re

Data Scientist, AI

Bloomington, IL · On-site +1

Act as a liaison between the ML Engineers and Data Science team, managing AI/ML model deployments and conducting testing. * Participate in the development of modeling presentations and present ...

State Farm

Data Scientist

Bloomington, IL · On-site

Our data science teams also embrace staying current with the evolving data science landscape ... Experience with at least one statistical programming language: SAS, R, and/or Python Other Things ...

State Farm

Data Scientist

Bloomington, IL · On-site

ET-D&AI provides data science support to internal business partners across State Farm, including ... Experience with at least one statistical programming language: Python, R, or SAS Other Things We ...

State Farm

Data Scientist

Bloomington, IL · Hybrid

Experience with at least one statistical programming language: SAS, R, and/or Python Other Things ... data science, quantitative marketing, operations research, industrial engineering, etc.

State Farm

Data Scientist

Bloomington, IL · Hybrid

Experience with at least one statistical programming language: SAS, R, and/or Python Other Things ... data science, quantitative marketing, operations research, industrial engineering, etc.

Pursuit Aerospace

Lead Data Scientist

Morton, IL · On-site

The lead data scientist will function like a forward-deployed engineer who takes a supply chain problem from ambiguity to financial impact: framing the problem, shaping the data and models, building ...

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Showing results 1-20

All JobsData Engineer JobsData Engineer Jobs in Bloomington, IL

Data Engineer information

See Bloomington, IL salary details

$42.7K

$124.4K

$170.3K

How much do data engineer jobs pay per year?

As of Aug 2, 2026, the average yearly pay for data engineer in Bloomington, IL is $124,428.00, according to ZipRecruiter salary data. Most workers in this role earn between $109,800.00 and $131,900.00 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.
More about Data Engineer jobs
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Data Engineer jobs near you
Infographic showing various Data Engineer job openings in Bloomington, IL as of July 2026, with employment types broken down into 100% Full Time. Highlights an 50% In-person, and 50% Hybrid job distribution, with an average salary of $124,428 per year, or $59.8 per hour.

Senior Data Engineer

1 point system

Normal, IL • On-site

$103K - $140K/yr

Contractor

Posted 18 days ago

Job description

Job Description

As a Sr. Data Engineer, you will help build and operate the data foundation that powers analytics across programs and sites. You will design and maintain scalable ingestion pipelines, develop well-modeled datasets, and ensure data quality and reliability across critical systems.

This role sits at the intersection of operational systems, modern data platform engineering, and analytics enablement, helping convert raw operational signals into governed, high-value datasets that power analytics applications, core metrics, and future AI-driven insights.

Roles and Responsibilities

  • Design, build, and operate data ingestion pipelines from operational, quality, test, and service systems into Databricks using Fivetran/AWS/Databricks and standardized ELT patterns.
  • Develop and maintain dbt models for operational, quality, and ramp metrics, following our standard patterns for analytics.
  • Set up and maintain data quality checks, audits, and monitoring for freshness, completeness, and contract compliance across key pipelines.
  • Optimize Databricks jobs, Fivetran connectors, and dbt runs for performance, cost, and reliability, including orchestration, alerting, and runbooks.
  • Collaborate with analytics engineers and product teams to turn models into highvalue data products powering analytics applications.
  • Contribute to the semantic layer and catalog so GenAI agents and self-service tools can reliably discover and query operational data.
  • Drive improvements in upstream systems and schemas to reduce data issues at the source.

Required Qualifications

  • 5+ years of experience in Data Engineering, Analytics Engineering, or Software Engineering working with production data systems.
  • Strong expertise in SQL and Python for building scalable data pipelines and transformations.
  • Hands-on experience building ELT pipelines using modern cloud data platforms (Databricks strongly preferred).
  • Deep experience with dbt, including model development, testing, documentation, and CI/CD integration.
  • Experience with managed ingestion tools such as Fivetran, Airbyte, or similar.
  • Experience designing and operating production-grade data pipelines with monitoring and observability.
  • Strong collaboration skills and ability to partner with engineering teams, analysts, and operational stakeholders.
  • Bachelors or Master’s degree in Computer Science, Engineering, Mathematics, or related field, or equivalent practical experience.

Preferred Qualifications

  • Experience working with manufacturing, MES, quality, or operational data.
  • Familiarity with Fivetran connector management and ingestion architecture.
  • Experience with data contracts and schema governance.
  • Experience building semantic layers or governed analytical datasets.
  • Exposure to modern analytics tools (Hex, Tableau, Power BI, or similar).
  • Experience enabling AI or advanced analytics use cases on top of operational data.
  • Knowledge of streaming or near-real-time data pipelines.