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Data Engineer Jobs in Chicago, IL (NOW HIRING)

Data Engineer

Chicago, IL

$165K - $175K/yr

Data Engineer Boston, Massachusetts, United States Job Openings Data Engineer Job Title: Data Engineer - AI Platform Location: Boston, Chicago, New York City, San Francisco, Silicon Valley ...

Data Engineer

Lisle, IL

$112K - $135K/yr

Support Data Engineering initiatives across two Data Engineering Teams: * Prospect Team * Student Team Contribute to stabilizing and scaling the Data Engineering organization Top 3 Requirements:

Data Engineer

Chicago, IL

$118K - $141K/yr

Big Data Engineer We are currently seeking a Big Data Engineer for an onsite position located in Charlotte, NC, Denver, CO, Jacksonville, FL, and Chicago, IL. This is a 12+ month W2 contract ...

Data Engineer

Chicago, IL

$118K - $141K/yr

Our capabilities range from Data Engineering, Visualization, Data Management to Advanced analytics, Big Data, Cloud and Machine Learning. Our uniqueness is in bringing the right mix of technology and ...

Data Engineer

Chicago, IL · On-site

$118K - $141K/yr

Our capabilities range from Data Engineering, Visualization, Data Management to Advanced analytics, Big Data, Cloud and Machine Learning. Our uniqueness is in bringing the right mix of technology and ...

Data Engineer

Chicago, IL · On-site

$118K - $141K/yr

Role : Data Engineer Location : Chicago, IL (3days onsite) Experience : Min. 10+ Years Client Interview - in-person in Chicago, IL. Must be strong on Complex sql queries and Databricks Seeking a ...

Data Engineer

Chicago, IL · Hybrid

$60 - $65/hr

Data Engineer Contract: Chicago, Illinois, US Salary Range: 60.00 - 64.00 | Per Hour Job Code: 369312 End Date: 2026-06-18 Days Left: 8 days, 3 hours left Apply Job Title: Senior Data Engineer ...

Data Engineer

Chicago, IL

$118K - $141K/yr

Data Engineer We are looking for a skilled Data Engineer to design and build scalable data solutions using PySpark and AWS services. The ideal candidate will have hands-on experience in building ...

Data Engineer

Chicago, IL

$118K - $141K/yr

Data Engineer - I The Data Engineer - I will be responsible for building and maintaining optimal data pipeline and reporting architecture for the next generation Data Warehouse, reporting, and data ...

Data Engineer

Chicago, IL

$118K - $141K/yr

Summary The Data Engineer, Solutions & Data role designs, builds, and operates data pipelines and data integration processes that translate raw data into trusted, usable datasets for analytics ...

Data Engineer

Chicago, IL · Hybrid

$118K - $141K/yr

Data Engineer Join a dynamic team in a hybrid role based in the Chicago area. Focus on designing and maintaining data pipelines using generic data processing platforms. Engage in building and ...

Data Engineer

Chicago, IL · On-site

$118K - $141K/yr

Data Engineer Location: Chicago, Ill Openings: 1 Type: Permanent hire The Client is searching for an experienced data engineer. This person will be responsible for building and managing an array of ...

Data Engineer

Chicago, IL · Hybrid

$118K - $141K/yr

Data Engineer Salary: Open + Bonus Location: Chicago, IL Hybrid: 3 days onsite, 2 days remote *We are unable to provide sponsorship for this role* Qualifications * Bachelor s degree * 3+ years of ...

Data Engineer

Bridgeview, IL

$116K - $140K/yr

The Data Engineer is a core technical leader within the data team, responsible for the design, architecture, and delivery of scalable, reliable data platforms that power the organization's data ...

Data Engineer

Bridgeview, IL

$116K - $140K/yr

The Data Engineer is a core technical leader within the data team, responsible for the design, architecture, and delivery of scalable, reliable data platforms that power the organization's data ...

Data Engineer

Bridgeview, IL · On-site

$116K - $140K/yr

The Data Engineer is a core technical leader within the data team, responsible for the design, architecture, and delivery of scalable, reliable data platforms that power the organization's data ...

Data Engineer

Chicago, IL

$118K - $141K/yr

Data Engineer Burnham, IL (100% onsite) Contract/Direct Hire We're looking for a Data Engineer who can step into an established environment and quickly take ownership of critical data workflows. This ...

Data Engineer

Burnham, IL · On-site

$118K - $141K/yr

Data Engineer Burnham, IL (100% onsite) Contract/Direct Hire We're looking for a Data Engineer who can step into an established environment and quickly take ownership of critical data workflows. This ...

Data Engineer

Chicago, IL · Remote

$118K - $141K/yr

Data Engineer - Data Catalog (Alation) Location: Chicago, IL (100% Remote) Duration: 6-12 Months Rate: DOE We are seeking an experienced Data Engineer with expertise in Alation for a 6-12 month ...

Data Engineer

Burnham, IL · On-site

$114K - $137K/yr

a { text-decoration: none; color: #464feb; } tr th, tr td { border: 1px solid #e6e6e6; } tr th { background-color: #f5f5f5; } Data Engineer Burnham, IL (100% onsite) Contract/Direct Hire We're ...

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Showing results 1-20

Data Engineer information

See Chicago, IL salary details

$45.8K

$133.6K

$182.9K

How much do data engineer jobs pay per year?

As of Jun 16, 2026, the average yearly pay for data engineer in Chicago, IL is $133,627.00, according to ZipRecruiter salary data. Most workers in this role earn between $118,000.00 and $141,600.00 per year, depending on experience, location, and employer.

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.

Are data engineers highly paid?

Data engineers are generally well-paid due to their specialized skills in designing and maintaining data infrastructure, with salaries often higher than many other IT roles. Compensation varies based on experience, location, and industry, but strong technical skills in programming, databases, and cloud platforms typically lead to higher earnings.

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 pipeline tools. Entry-level data engineering positions may be available for candidates with relevant internships or strong foundational skills in SQL, Python, or cloud platforms, but most roles expect some prior experience. Certifications or coursework in data management can also be beneficial for those starting out.

What engineer makes $500,000 a year?

Senior data engineers with extensive experience, advanced skills in big data tools, and leadership roles can earn salaries approaching or exceeding $500,000 annually, especially in high-cost-of-living areas or large tech companies. Such compensation often includes base salary, bonuses, and stock options. Achieving this level typically requires years of expertise and a strong track record in data architecture and engineering.
What are the most commonly searched types of Data Engineer jobs in Chicago, IL? The most popular types of Data Engineer jobs in Chicago, IL are:
What job categories do people searching Data Engineer jobs in Chicago, IL look for? The top searched job categories for Data Engineer jobs in Chicago, IL are:
What cities near Chicago, IL are hiring for Data Engineer jobs? Cities near Chicago, IL with the most Data Engineer job openings:
Infographic showing various Data Engineer job openings in Chicago, IL as of June 2026, with employment types broken down into 89% Full Time, and 11% Contract. Highlights an 89% In-person, and 11% Remote job distribution, with an average salary of $133,627 per year, or $64.2 per hour.

$165K - $175K/yr

Other

Posted 7 days ago


Job description

Data Engineer

Boston, Massachusetts, United States Job Openings Data Engineer

Job Title: Data Engineer - AI Platform

Location: Boston, Chicago, New York City, San Francisco, Silicon Valley, Washington DC

Number of openings: 1

Experience: 5+ years of professional experience as a data engineer

Salary: $165,000 - $175,000

Clearance: Secret (prefer TS)

Position Summary

We are hiring a skilled Data Engineer to contribute to the development of a sophisticated AI-powered platform that supports advanced, data-driven solutions. This role offers the opportunity to work on cutting-edge initiatives involving generative AI, large-scale data systems, and cloud-native architectures.

You will partner with a multidisciplinary team of engineers, data scientists, and product stakeholders to design and implement scalable data infrastructure. The primary focus will be enabling platform capabilities tailored for government and defense-related environments.

Key Responsibilities
  • Design and build robust data ingestion and processing pipelines to support AI and GenAI applications
  • Develop and maintain high-quality Python-based data workflows, including testing and validation
  • Collaborate with cross-functional teams including software engineers, data scientists, and UI/UX designers
  • Implement and enhance CI/CD pipelines (including GitHub Actions) to streamline deployment and integration processes
  • Work across multi-cloud environments (AWS primarily; exposure to Azure and GCP is beneficial)
  • Utilize containerization technologies (Docker) to support scalable and portable deployments
  • Contribute to the development and optimization of data systems used by generative AI applications
  • Ensure performance, reliability, and scalability of data pipelines through monitoring and diagnostics
What You'll Experience
  • Opportunity to work on high-impact AI platform initiatives
  • A fast-paced, performance-driven environment with strong technical mentorship
  • Continuous learning through structured development programs and real-world problem solving
  • A collaborative culture that values innovation, ownership, and diverse perspectives
  • Exposure to globally distributed teams and modern engineering practices
  • Competitive compensation along with a comprehensive benefits package
Required Qualifications
  • U.S. Citizenship is required
  • Prior experience supporting defense or government environments, including handling classified or sensitive data
  • Active Secret clearance required (Top Secret or higher preferred)
  • 5+ years of experience in data engineering, with a strong focus on cloud-based solutions
Technical Skills & Expertise
  • Strong proficiency in Python for data engineering and pipeline development
  • Hands-on experience with AWS-based data engineering (experience with Azure or GCP is a plus)
  • Deep understanding of data modeling, data ingestion frameworks, and pipeline architecture
  • Experience working with knowledge graphs, particularly using Neo4j, and familiarity with relational databases
  • Expertise in writing clean, maintainable, and testable code, including automation and error handling best practices
  • Practical experience with Docker and containerized workflows
  • Strong background in data pipeline performance tuning, monitoring, and troubleshooting
  • Excellent analytical and problem-solving capabilities
  • Effective communication skills and ability to collaborate within cross-functional teams