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Remote Ai Data Engineer Jobs in Chicago, IL (NOW HIRING)

Remote As a Senior Lead, Data Engineering, you will serve as a technical leader who helps shape the ... Identify and implement AI-enabled approaches that accelerate development, improve data quality ...

Data Engineer

Chicago, IL · On-site +1

$118K - $141K/yr

Data Engineer - Inspire11 Elevens, as we call ourselves here, are curiously smart, creative, and ... Develop AI-first, cloud-native data solutions using Microsoft Fabric, Databricks, Snowflake, and ...

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 ... Influence how data powers analytics, reporting, and AI across the company Responsibilities What You ...

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 ... Influence how data powers analytics, reporting, and AI across the company Responsibilities What You ...

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 ... Influence how data powers analytics, reporting, and AI across the company Responsibilities What You ...

Associate Data Engineer

Naperville, IL · Remote

$114K - $137K/yr

About the Role We're looking for an Associate Data Engineer to join our team and help make data ... Comfort working in a remote, collaborative environment * Based in the United States (preferred time ...

Data Engineer

Chicago, IL · On-site +1

$118K - $141K/yr

With offices in Chicago, Miami, and around the world through the power of remote work, we are a ... Job Summary We are looking for a Data Engineer to join a team of analytics and machine learning ...

Data Engineer

Chicago, IL · On-site +1

$100K - $145K/yr

With offices in Chicago, Miami, and around the world through the power of remote work, we are a ... Job Summary We are looking for a Data Engineer to join a team of analytics and machine learning ...

Data Engineer

Chicago, IL · On-site +1

$100K - $145K/yr

With offices in Chicago, Miami, and around the world through the power of remote work, we are a ... Job Summary We are looking for a Data Engineer to join a team of analytics and machine learning ...

Lead Data Engineer

Chicago, IL · Remote

$105K - $139K/yr

Lead Data Engineer | Build the Future of Data at GATX Remote (Chicago-area preferred) Founded in ... Influence how data powers analytics, reporting, and AI across the company What You'll Be Doing

Lead Data Engineer

Chicago, IL · On-site +1

$140K - $180K/yr

Lead Data Engineer Firm Overview Hinshaw & Culbertson LLP is a national law firm with more than 500 ... Evaluate emerging data, analytics, and AI capabilities and lead proof-of-concepts that improve ...

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Remote Ai Data Engineer information

See Chicago, IL salary details

$45.8K

$133.6K

$182.9K

How much do remote ai data engineer jobs pay per year?

As of Aug 10, 2026, the average yearly pay for remote ai 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 are some common challenges faced by remote AI data engineers, and how can they be addressed?

Remote AI Data Engineers often encounter challenges such as coordinating with cross-functional teams across different time zones, ensuring data security when accessing sensitive datasets remotely, and maintaining effective communication for project updates. To address these, it's important to establish clear protocols for data sharing, leverage collaboration tools (like Slack or Jira), and schedule regular check-ins to align with team goals. Adopting strong version control practices and automated testing can also help streamline workflows and minimize errors in a distributed environment.

What is the difference between Remote Ai Data Engineer vs Data Scientist?

AspectRemote Ai Data EngineerData Scientist
Required CredentialsBachelor's in CS, Data Engineering, or related; experience with cloud platformsBachelor's or higher in CS, Statistics, or related; strong analytical skills
Work EnvironmentData pipelines, cloud infrastructure, codingData analysis, statistical modeling, visualization
Employer & Industry UsageTech companies, AI firms, startupsResearch institutions, tech companies, finance
Common Search & ComparisonYesYes

Remote Ai Data Engineers focus on building and maintaining data pipelines and infrastructure for AI applications, requiring skills in data engineering and cloud platforms. Data Scientists analyze data, develop models, and generate insights. While both roles work with data, Data Engineers prepare the data environment, whereas Data Scientists interpret and model the data. They often collaborate but serve different functions in AI and data projects.

What is a remote AI data engineer?

A Remote AI Data Engineer is a professional who designs, builds, and maintains data pipelines and infrastructure to support artificial intelligence (AI) and machine learning (ML) projects, all while working from a remote location. They are responsible for collecting, cleaning, transforming, and storing large datasets, ensuring data quality and accessibility for AI applications. These engineers collaborate with data scientists, software engineers, and stakeholders to deliver data solutions that power intelligent systems, often leveraging cloud technologies and distributed computing. Their work enables organizations to harness data for predictive analytics, automation, and decision-making—without being tied to a physical office.

What are the key skills and qualifications needed to thrive as a remote AI data engineer?

To thrive as a Remote AI Data Engineer, you need strong programming skills (Python, SQL), a solid understanding of data structures, machine learning principles, and typically a degree in computer science or related fields. Familiarity with big data platforms (such as Hadoop or Spark), cloud services (AWS, GCP, or Azure), and experience with AI/ML frameworks like TensorFlow or PyTorch are commonly required. Excellent problem-solving, communication, and self-motivation skills help you collaborate effectively and manage projects independently in a remote setting. These skills and qualities ensure robust AI data pipelines, effective model deployment, and seamless teamwork across distributed environments.
What are the most commonly searched types of Ai Data Engineer jobs in Chicago, IL? The most popular types of Ai Data Engineer jobs in Chicago, IL are:
What are popular job titles related to Remote Ai Data Engineer jobs in Chicago, IL? For Remote Ai Data Engineer jobs in Chicago, IL, the most frequently searched job titles are:
What job categories do people searching Remote Ai Data Engineer jobs in Chicago, IL look for? The top searched job categories for Remote Ai Data Engineer jobs in Chicago, IL are:
What cities near Chicago, IL are hiring for Remote Ai Data Engineer jobs? Cities near Chicago, IL with the most Remote Ai Data Engineer job openings:
Infographic showing various Remote Ai Data Engineer job openings in Chicago, IL as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $133,627 per year, or $64.2 per hour.

Senior Lead Data Engineer (Remote)

Stryker

Chicago, IL • On-site, Remote

Full-time

Posted 7 days ago


Job description

Work Flexibility: Remote

As a Senior Lead, Data Engineering, you will serve as a technical leader who helps shape the future of enterprise data solutions. In this role, you will drive complex data initiatives, influence technical strategy, and partner with teams across the organization to build scalable, high-impact data products. This is an opportunity to solve challenging business problems while mentoring fellow engineers and elevating data engineering best practices.

What You Will Do

  • Lead the architecture, development, and modernization of scalable enterprise data platforms that support global procurement analytics and business transformation.
  • Define and help execute a multi-year data engineering strategy focused on platform scalability, reliability, automation, technical debt reduction, and long-term maintainability.
  • Design, build, and optimize Azure-based data solutions using technologies such as Databricks, Delta Lake, Azure Data Factory, Azure DevOps, CI/CD pipelines, and infrastructure automation.
  • Integrate and harmonize data across multiple ERP systems by standardizing supplier, purchasing, and master data into common enterprise data models.
  • Partner with procurement analysts, architects, engineers, and business stakeholders to translate complex business needs into reusable, scalable data products and engineering solutions.
  • Establish engineering standards, conduct architecture reviews, improve documentation, and mentor engineers to raise the overall technical capability of the team.
  • Identify and implement AI-enabled approaches that accelerate development, improve data quality, automate documentation, support testing, and enhance analyst productivity.
  • Evaluate and recommend tools, frameworks, patterns, and platform investments that improve performance, reliability, security, governance, and operational efficiency.
  • Support the development of internal data products, APIs, and user-facing applications that simplify access to procurement insights and improve analyst productivity.
  • Present technical recommendations, roadmap priorities, tradeoffs, and business impacts to technical and non-technical stakeholders, including leadership teams.

What you need

Required

  • Bachelor's degree in Computer Science, Data Engineering, Data Science, Information Systems, Mathematics, Statistics, or a related technical field.
  • 6+ years of experience in data engineering, analytics engineering, software engineering, or enterprise data platform development.
  • Proven experience architecting, building, and modernizing scalable cloud-based data platforms in an enterprise environment.
  • Hands-on experience with Azure-based data engineering technologies, including Databricks, Delta Lake, Azure Data Factory, Azure DevOps, CI/CD pipelines, and infrastructure automation.
  • Strong proficiency in SQL and Python, with experience using Spark or similar distributed data processing frameworks.
  • Experience designing reliable ETL/ELT pipelines, data warehouse or Lakehouse architectures, data models, and performance-optimized analytics solutions.
  • Experience integrating data from multiple ERP or enterprise source systems and harmonizing inconsistent master, supplier, purchasing, or transactional data into common data models.
  • Experience with API integrations, REST services, authentication, security, data governance, and production support practices.
  • Demonstrated ability to establish engineering standards, conduct architecture reviews, improve documentation, mentor engineers, and influence technical direction without direct authority.
  • Ability to partner with analysts, engineers, architects, and business stakeholders to translate complex business requirements into scalable, maintainable engineering solutions.

Preferred

  • Master's degree in Computer Science, Data Engineering, Data Science, Information Systems, Business Analytics, or a related technical field.
  • Experience supporting procurement, supply chain, manufacturing, finance, or ERP analytics in a global enterprise environment.
  • Experience building or modernizing enterprise data platforms, Lakehouse architectures, or cloud analytics ecosystems at scale.
  • Hands-on experience with multiple ERP platforms, such as SAP ECC, SAP S/4HANA, Oracle, JD Edwards, Infor, QAD, or Microsoft Dynamics.
  • Full-stack engineering experience, including React, Next.js, Vercel, API development, authentication, and internal web application development.
  • Experience using AI-assisted engineering tools and workflows, such as GitHub Copilot, ChatGPT, Claude, Cursor, AI coding agents, AI-assisted testing, or AI-assisted documentation.
  • Experience designing internal tools, data products, APIs, or analyst-facing applications that improve productivity and simplify access to insights.
  • Experience leading cloud modernization, platform migration, technical debt reduction, automation, or data quality improvement initiatives.
  • Experience with Power BI, Tableau, or similar business intelligence and visualization tools.
  • Demonstrated curiosity and continuous learning mindset, with a track record of experimenting with emerging technologies and applying them to practical engineering or analytics use cases.

United States of America Pay Ranges:

  • USN: $118,000 - $196,700 USD Annual
  • US5: $123,900 - $206,500 USD Annual
  • US10: $129,800 - $216,400 USD Annual
  • US15: $135,700 - $226,200 USD Annual
  • US20: $141,600 - $236,000 USD Annual
  • US30: $153,400 - $255,700 USD Annual
View the U.S. work location and transparency guide to find the pay range for your location.

Travel Percentage: 10%Stryker Corporation is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, ethnicity, color, religion, sex, gender identity, sexual orientation, national origin, disability, or protected veteran status. Stryker is an EO employer - M/F/Veteran/Disability.Stryker Corporation will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with the contractor's legal duty to furnish information.