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Remote Data Engineering Jobs in Illinois (NOW HIRING)

Kemper

Principal Data Engineer

Downers Grove, IL · On-site +1

Location(s) Chicago, Illinois, Downers Grove, Illinois, Remote-AL, Remote-CT, Remote-FL, Remote-GA ... This role provides hands-on technical leadership across data engineering initiatives, cloud ...

Kemper

Principal Data Engineer

Chicago, IL · On-site +1

Location(s) Chicago, Illinois, Downers Grove, Illinois, Remote-AL, Remote-CT, Remote-FL, Remote-GA ... This role provides hands-on technical leadership across data engineering initiatives, cloud ...

MSR Technology Group

ETL Data Engineer

Springfield, IL · Remote

$113K - $136K/yr

Senior Data Engineer - Azure / Python ETL Modernization Remote (U.S.) with Minimal travel (2-3x per year) Overview We're hiring a Senior Data Engineer to lead enterprise ETL modernization initiatives ...

Collectiv

Data Engineer (Azure, Fabric, Databricks)

Chicago, IL · On-site +1

$118K - $141K/yr

Ensure data quality, reliability, and usability across the analytics platform Engineering Best ... At Collectiv, your career thrives with a perfect blend of remote flexibility, growth potential, and ...

Bright Vision Technologies

AI Data Engineer

Bolingbrook, IL · Remote

$113K - $136K/yr

AI Data Engineer Location: 100% Remote (Continental United States) Position Type: In-house Bright Vision Technologies SOW engagement (no third-party client or vendor) Experience: 6+ years Salary ...

Cohort AI Inc.

Associate Data Engineer

Naperville, IL · Remote

$114K - $137K/yr

This is a great opportunity if you're early in your data engineering career and enjoy working hands ... Comfort working in a remote, collaborative environment * Based in the United States (preferred time ...

TEKsystems

Data Engineer

Deerfield, IL · Remote

$70 - $85/hr

Engineering Teams * Responsible for shaping how data is structured, stored, and consumed * Expected ... remote position. Application Deadline This position is anticipated to close on Jun 30, 2026. About ...

GATX

Lead Data Engineer

Chicago, IL · On-site +1

$111K - $160K/yr

Lead Data Engineer | Build the Future of Data at GATX Remote (Chicago-area preferred) Founded in 1898 and headquartered in Chicago, IL, GATX Corporation (NYSE: GATX) is an industry leader with 125 ...

GATX

Lead Data Engineer

Chicago, IL · On-site +1

$111K - $160K/yr

Overview Lead Data Engineer | Build the Future of Data at GATX Remote (Chicago-area preferred) Founded in 1898 and headquartered in Chicago, IL, GATX Corporation (NYSE: GATX) is an industry leader ...

GATX

Lead Data Engineer

Chicago, IL · On-site +1

$111K - $160K/yr

Overview Lead Data Engineer | Build the Future of Data at GATX Remote (Chicago-area preferred) Founded in 1898 and headquartered in Chicago, IL, GATX Corporation (NYSE: GATX) is an industry leader ...

GATX

Lead Data Engineer

Chicago, IL · On-site +1

$111K - $160K/yr

Overview Lead Data Engineer | Build the Future of Data at GATX Remote (Chicago-area preferred) Founded in 1898 and headquartered in Chicago, IL, GATX Corporation (NYSE: GATX) is an industry leader ...

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All JobsData Engineering JobsRemote Data Engineering JobsRemote Data Engineering Jobs in Illinois

Remote Data Engineering information

See Illinois salary details

$43.1K

$125.7K

$172K

How much do remote data engineering jobs pay per year?

As of Jul 6, 2026, the average yearly pay for remote data engineering in Illinois is $125,698.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,000.00 and $133,200.00 per year, depending on experience, location, and employer.

Can I work remotely as a data engineer?

Yes, remote data engineering roles are common, allowing professionals to work from various locations. These jobs often require skills in cloud platforms, programming, and data pipeline tools, and may involve collaboration through online communication tools.

How do remote data engineers typically collaborate with other team members across different time zones?

Remote data engineers often work with distributed teams, which requires strong communication and organization skills. They collaborate using tools like Slack, Zoom, and project management platforms to stay aligned on data pipeline development, troubleshooting, and deployment. Regular stand-ups, asynchronous documentation, and clear communication of progress are essential for ensuring everyone is on the same page, regardless of location. Flexibility in working hours and proactive scheduling of meetings help facilitate effective collaboration and project delivery.

What is remote data engineering?

Remote data engineering involves designing, building, and maintaining data systems and pipelines while working from a location outside of a traditional office. Remote data engineers use tools to collect, process, and store large sets of data, making it accessible for analysis and business decision-making. They collaborate with teams virtually, often using cloud-based technologies, to ensure that data infrastructure is reliable, scalable, and secure. This role requires strong technical skills in programming, databases, and data architecture, as well as the ability to communicate effectively in a distributed work environment.

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

To thrive as a Remote Data Engineer, you need strong programming skills (such as Python, Java, or Scala), experience with data modeling, ETL processes, and a solid understanding of database systems, often supported by a degree in computer science or a related field. Proficiency with big data tools like Apache Spark, Hadoop, cloud platforms (AWS, Azure, GCP), and certifications in these technologies is highly valued. Excellent problem-solving abilities, self-motivation, and clear communication are crucial soft skills for remote collaboration and project delivery. These competencies ensure effective data pipeline development, reliable data management, and seamless teamwork across distributed environments.

What engineer makes $500,000 a year?

Senior data engineers with extensive experience, advanced skills in cloud platforms, and expertise in big data tools 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.

How to make $1000 a week remote?

Remote data engineers can earn $1000 or more per week by working on high-demand projects, leveraging specialized skills in data pipelines, cloud platforms, and programming languages like Python or SQL. Building a strong portfolio, obtaining relevant certifications, and working with multiple clients or on freelance platforms can help increase weekly income. Consistent remote work and advanced expertise are key to reaching this earning level.

Is AI replacing data engineers?

AI is automating certain tasks within data engineering, such as data cleaning and pipeline management, but it does not replace the need for data engineers. Data engineers are essential for designing, building, and maintaining complex data systems, and their expertise in tools like SQL, Python, and cloud platforms remains critical for managing data workflows effectively.

What is the difference between Remote Data Engineering vs Remote Data Analyst?

AspectRemote Data EngineeringRemote Data Analyst
Required CredentialsBachelor's in CS, Data Science, or related field; experience with SQL, Python, cloud platformsBachelor's in Statistics, Data Science, or related; proficiency in Excel, SQL, visualization tools
Work EnvironmentBuilds data pipelines, manages databases, works with cloud infrastructureAnalyzes data sets, creates reports, visualizes data insights
Employer & Industry UsageTech companies, finance, healthcare, e-commerceMarketing agencies, finance, retail, consulting

Remote Data Engineering focuses on designing and maintaining data infrastructure, while Remote Data Analysts interpret data to provide insights. Both roles require strong analytical skills but differ in technical depth and responsibilities.

What are the most commonly searched types of Data Engineering jobs in Illinois? The most popular types of Data Engineering jobs in Illinois are:
What are popular job titles related to Remote Data Engineering jobs in Illinois? For Remote Data Engineering jobs in Illinois, the most frequently searched job titles are:
What job categories do people searching Remote Data Engineering jobs in Illinois look for? The top searched job categories for Remote Data Engineering jobs in Illinois are:
What cities in Illinois are hiring for Remote Data Engineering jobs? Cities in Illinois with the most Remote Data Engineering job openings:
Remote Data Engineering jobs near you
Infographic showing various Remote Data Engineering job openings in Illinois as of July 2026, with employment types broken down into 78% Full Time, 11% Part Time, and 11% Contract. Highlights an 100% Remote job distribution, with an average salary of $125,698 per year, or $60.4 per hour.
Manager, Data Engineering- Data Visualization (Remote)

Manager, Data Engineering- Data Visualization (Remote)

Inspira Financial

Oak Brook, IL • On-site, Remote

Full-time

Posted 2 days ago

Inspira Financial rating

7.2

Company rating: 7.2 out of 10

Based on 20 frontline employees who took The Breakroom Quiz

Job description

The Data Engineering Manager - Enterprise Data Visualization will report to the Sr. Director, Data Engineering in the Technology Department. This role will engage with Business Leaders, Analysts, Data Stewards, Application Architects, and third-party providers. This role will lead an agile team of Data Engineers that work to enhance data delivery, quality, accessibility, and analysis. This role will improve functionality, streamline data processes, provide direct support to the business and operational teams, and strengthen targeted business strategies. The role works closely with the Business, Operations and Technology groups to help design and lead the development and maintenance of the Enterprise Reporting Platform.
If you are ready to advance your career and contribute to a rapidly growing company dedicated to delivering innovative products and ensuring an exceptional client experience, we eagerly await your application!
Duties & Responsibilities:
  • Lead an agile team of data engineers with varying levels of experience in the delivery of enterprise data initiatives.
  • Oversee the creation of data visualizations including enterprise dashboards, analytical, and operational reporting.
  • Partner with business leadership to implement 3-5-year plan for area of responsibility.
  • Manage multiple concurrent projects.
  • Define and establish benchmarks, metrics, and quality measures.
  • Support disaster recovery and contingency planning.
  • Ensure solutions meet non-functional requirements, including security, performance, maintainability, scalability, usability, and reliability.
  • Effectively manage relevant 3rd party vendor relationships.
  • Support the stability and resiliency of Data Visualization production processes, as well as instituting a robust support model addressing process and application failures.
  • Understand the business and technology.
  • Drive process alignment with business partners.
  • Identify project team requirements and capital requirements.
  • Evaluate and integrate productivity tools, development tools, testing tools, databases, and applications into this architecture.
  • Work with the leaders of Technology Infrastructure and Software Engineering to ensure effective operational tools and procedures are in place to support the application architecture.
  • Research and strategize emerging technologies relevant to business needs.
  • Develop and document an overall enterprise reporting delivery architecture which is fit for business purposes and cost effective.

Supervisory Responsibilities:
  • Recruits, interviews, hires, and trains new staff.
  • Oversees the daily workflow of the department.
  • Provides constructive and timely performance evaluations.
  • Participate in budget planning and monitoring.

Education & Experience:
  • 10+ years of experience in Data Engineering, Data Visualization, or Software Product Development
  • Bachelor's degree preferred in Computer Science, Computer Engineering, Software Engineering, Electrical/Electronic Engineering, Mathematics, Statistics, Data Science, or similar/related Engineering/Science based disciplines
  • 1-3 years of leadership experience managing direct reports
  • Tableau Certifications are preferred
  • Microsoft Certified Azure Data Fundamentals preferred
  • Snowflake SnowPro Certification preferred

Skills & Abilities:
  • Strong understanding of Programming Skills. While not expected to perform day-to-day code development, the Data Engineering Manager is expected to be knowledgeable and practiced in programming languages such as SQL/T-SQL, Python
  • Data / Database Skills: Competence with relational and NoSQL databases (e.g., SQL Server, MongoDB) including proficiency with Data Definition Languages, Data Mark-Up Languages
  • Participate in design and implementation of OLAP databases to serve internal and external consumer use cases
  • Design and implement hybrid data cloud services, leveraging public could providers (i.e., Azure) and specialty providers (i.e., Snowflake)
  • Understand and implement Generative AI solutions within the context of developer assistance and data visualization product delivery
  • Support the development of enterprise data visualization strategy ensuring rapid delivery while taking responsibility for applying standards, principles, theories, and concepts
  • Support enterprise data governance initiatives
  • Strong experience in working with and optimizing enterprise reporting
  • Exceptional analytical skills and strong attention to detail
  • Ability to prioritize, plan and take initiative
  • Highly self-motivated and directed
  • Experience in a high availability environment preferred
  • Knowledge of ITIL/ITSM Foundational practices and framework preferred
  • Strong Vendor management skills preferred
  • Strong understanding of Salesforce Financial Services Cloud data object model preferred
  • Data Engineering Tools/Platforms
    • Platform/Framework (Snowflake, Azure MSSQL)
    • Visualization (Tableau, PowerBI, SSRS)
    • Governance (Data.World, Atlan, Alation)
  • Problem-Solving and Analytical Skills: Data engineers must possess strong problem-solving abilities and the capacity to analyze complex technical challenges. They should be able to break down problems into manageable components and devise effective solutions
  • Software Product Development Lifecycle: Familiarity with the software development lifecycle (SDLC) is crucial. This includes understanding requirements gathering, system design, implementation, testing, deployment, and maintenance in an Agile/Scaled Agile manner. Experience with Scrum, Kanban, Extreme Programming, or other outcome based iterative development approach required
  • Knowledge of Development Tools and Frameworks: Data engineers should be proficient in using development tools and frameworks relevant to their domain. This can include version control systems (e.g., Git), integrated development environments (e.g., Visual Studio Code, IntelliJ), and frameworks specific to data platform development
  • Collaboration and Communication: Effective collaboration with cross-functional teams is vital for data engineers. Strong communication skills, both written and verbal, enable them to clearly express ideas, collaborate with colleagues, and convey technical concepts to non-technical stakeholders
  • Continuous Learning: The field of software engineering is constantly evolving, so a mindset of continuous learning is crucial. Staying updated with new technologies, programming languages, frameworks, and industry trends is highly valued
  • Testing and Debugging: Proficiency in automated software testing techniques, including unit testing, integration testing, and debugging, is important for ensuring the reliability and quality of software applications
  • Knowledge of Security Best Practices: Strong understanding of secure coding practices and the ability to apply them effectively in software development. Ability to implement security controls, conduct code reviews, and perform security-focused testing, ensuring adherence to industry standards and minimizing the risk of potential exploits
  • Compliance: Familiarity with regulatory compliance requirements and industry-specific security standards, such as GDPR, HIPAA, PCI-DSS, and ISO 27001. Ability to design and implement software solutions that meet these compliance standards, ensuring the protection of sensitive data and maintaining regulatory compliance
  • System Design and Architecture: Data engineers should have a solid understanding of data platform system design principles and architecture patterns. This includes scalability, performance optimization, and the ability to design robust and efficient software systems
  • Adaptability and Flexibility: Data engineers often encounter changing requirements, tight deadlines, and evolving technologies. Being adaptable, flexible, and able to quickly learn and adapt to new tools and frameworks is crucial

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