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Data Ops Manager Jobs in Chicago, IL (NOW HIRING)

Data Engineering Principal

Chicago, IL ยท On-site

$150 - $210/hr

... management, and cost/performance tradeoffs. * Drive data integrity through anomaly detection ... as invoicing, ops data feeds, and reporting utilities. * Apply AI and LLM-based tooling ...

Patient Access Ops Coordinator

Winfield, IL ยท On-site

$16.50 - $21/hr

  • Retirement

Coordinates and manages staff scheduling and coverage to accomplish optimum coverage. This may ... Understands minimum data set required for a complete registration, collects and verifies critical ...

Operations Management - Ops Coordinator, Work Order Coordinator, Ops Management, Planners, Safety ... For more information about how JLL processes your personal data, please view our Candidate Privacy ...

Finance Lead, FP&A - US Site Ops

North Chicago, IL ยท On-site

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Load and maintain financial Plan and Benchmark data in BPC. * Create, update, and maintain internal ... Significant interaction with US Site Ops Senior Management, Commercial, R&D Finance Partners ...

Machine Learning Engineering Manager

Chicago, IL ยท On-site

$118 - $153/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

... management and accuracy. Completes programming and implements efficiencies, performs testing and ... Ops team familiar with large cloud environments, Big Data technologies * 3+ years in software ...

Showing results 41-60

Data Ops Manager information

See Chicago, IL salary details

$31.9K

$100.1K

$177.2K

How much do data ops manager jobs pay per year?

As of Aug 19, 2026, the average yearly pay for data ops manager in Chicago, IL is $100,073.00, according to ZipRecruiter salary data. Most workers in this role earn between $68,000.00 and $129,300.00 per year, depending on experience, location, and employer.

What is a Data Ops manager?

Data Ops Managers are professionals responsible for overseeing the processes, tools, and teams involved in managing and optimizing data operations within an organization. They ensure the smooth flow, quality, and accessibility of data across various platforms and departments. Their role often includes automating data pipelines, implementing data governance practices, and collaborating with data engineers, analysts, and business stakeholders to support data-driven decision making.

What are some common challenges faced by a Data Ops manager, and how can they be addressed?

Data Ops Managers often encounter challenges such as coordinating across multiple teams, ensuring data quality, and managing fast-evolving data pipelines. Success in this role requires strong communication skills to align stakeholders, robust processes for monitoring data workflows, and the ability to quickly troubleshoot issues when data delivery is disrupted. Adopting automation tools and fostering a culture of continuous improvement can help Data Ops Managers maintain reliable, scalable systems while supporting organizational data needs.

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

To excel as a Data Ops Manager, you need a deep understanding of data management, analytics workflows, and process automation, often supported by a degree in computer science or a related field. Familiarity with tools like SQL, Python, cloud platforms (AWS, Azure), and orchestration systems such as Apache Airflow is typically required, along with certifications in data management or cloud services. Strong leadership, problem-solving, and communication skills help coordinate cross-functional teams and drive data initiatives. These competencies are crucial for ensuring data reliability, optimizing data pipelines, and enabling data-driven decision-making across the organization.

What is the difference between Data Ops Manager vs Data Engineer?

AspectData Ops ManagerData Engineer
Primary FocusOversees data operations, workflows, and process optimizationBuilds, constructs, and maintains data pipelines and infrastructure
Required SkillsData management, process improvement, team coordinationProgramming, database systems, ETL development
CertificationsData management, cloud certifications often preferredSQL, cloud platform certifications, programming languages
Work EnvironmentCollaborates with data teams, operations, and business unitsWorks closely with data scientists, analysts, and developers

While both roles involve working with data, the Data Ops Manager focuses on managing data workflows and operational efficiency, whereas the Data Engineer concentrates on building and maintaining data infrastructure. Understanding these differences helps in choosing the right career path or hiring the appropriate professional for your data needs.

What are popular job titles related to Data Ops Manager jobs in Chicago, IL?

For Data Ops Manager jobs in Chicago, IL, the most frequently searched job titles are:

What job categories do people searching Data Ops Manager jobs in Chicago, IL look for?

The top searched job categories for Data Ops Manager jobs in Chicago, IL are:

Infographic showing various Data Ops Manager job openings in Chicago, IL as of August 2026, with employment types broken down into 83% Full Time, 16% Part Time, and 1% Contract. Highlights an 84% Physical, 3% Hybrid, and 13% Remote job distribution, with an average salary of $100,073 per year, or $48.1 per hour.

Engineer II, Machine Learning Ops CBM Lab

Sralab

Chicago, IL โ€ข On-site

Full-time

Re-posted 7 hours ago


Job description

Shirley Ryan AbilityLab is the global leader in physical medicine and rehabilitation for adults and children with the most severe, complex conditions. By joining our team, you'll be part of our life-changing mission and vision. You'll contribute to an innovative, multifaceted culture that is second to none - one that embraces collaboration, excellence, discovery and compassion. You'll play a role in something that's never been done before as we integrate science and clinical care to help patients achieve better, faster outcomes - as we Advance Human Ability, together.

Job Description Summary

The Machine Learning Ops Engineer II works under general supervision and plays an active role in the design, development, and/or operationalization of machine learning models. This position involves responsibility in planning and managing artificial intelligence (AI) and machine learning (ML) lifecycle processes and contributing to the efficiency and effectiveness of deployed models.
The Machine Learning Ops Engineer II will consistently demonstrate support of the Shirley Ryan AbilityLab statement of Vision, Mission and Core Values by striving for excellence, contributing to the team efforts and showing respect and compassion for patients and their families, fellow employees, and all others with whom there is contact at or in the interest of the institute.
The Machine Learning Ops Engineer II will demonstrate Shirley Ryan AbilityLab Core Attributes: Communication, Accountability, Flexibility/Adaptability, Judgment/Problem Solving, Customer Service and Core Values (Hope, Compassion, Discovery, Collaboration, and Commitment to Excellence) while fulfilling job duties.

Job Description

The Machine Learning Engineer II will:

  • Actively participates in deploying, monitoring, and scaling machine learning models in production and big data research.

  • Evaluate data sets to determine suitability for applying machine learning models and techniques.

  • Guide and assist with the collection and curation of clinical datasets.

  • Assist in the implementation and evaluation of machine learning algorithms.

  • Develop and maintain continuous integration and continuous deployment pipelines for automated training and deployment of machine learning models.

  • Manage machine learning infrastructure and optimizes resource utilization.

  • Implement monitoring solutions for model performance and health.

  • Lead small projects or initiatives related to machine learning operations.

  • Work collaboratively with data scientists to optimize model performance.

  • Advocate for best practices in machine learning operations within the team.

  • Participate in maintaining a safe work environment through adherence to policies and procedures relative to safety, fire prevention, hazard communications, security, equipment use and maintenance, infection control and vehicle safety.

  • Perform all other duties that may be assigned in the best interest of the Shirley Ryan AbilityLab.

Reporting Relationships:

  • Reports directly to a designed engineering manager.

Knowledge, Skills & Abilities Required

  • A professional level of knowledge in computer science, engineering or a related field, typically acquired through a Bachelor's Degree.

  • Minimum of 3 years of related experience working on problems of moderate scope where analysis of situations or data requires a review of a variety of factors.

  • Continues to develop professional expertise, applying institute policies and procedures to resolve a variety of issues.

  • Proficient in using version control systems, especially Git.

  • Able to manage branches, handle merge conflicts, and understand the importance of commit history and reverting changes.

  • Strong skills in Python and experience with machine learning frameworks.

  • Working proficiency with Linux and Windows operating systems.

  • Familiarity with tools for deploying machine learning pipelines (eg Docker, Kubenates).

  • Familiarity with cloud based production pipelines offered by leading manufacturers (eg Microsoft Azure, Amazon Web Services, Google Cloud, etc).

  • Ability to work independently on assigned tasks and lead small projects. Excellent problem-solving skills and the ability to troubleshoot complex issues.

  • Good communication skills in both written and verbal forms. Able to work with research subjects and clinicians in a clinical setting.

  • Able to take direction and complete defined tasks in addition to anticipating and executing follow-up actions.

  • Able to perform assignments by receiving general instructions on routine work, and detailed instructions on new projects or assignments.

  • Able to exercise judgment within defined procedures and practices to determine appropriate action.

  • Able to build stable working relationships with multidisciplinary team.

Working Conditions

  • Normal office environment with little or no exposure to dust or extreme temperature.

The above statements are intended to describe the general nature and level of work being performed by people assigned to this classification. They are not intended to be construed as an exhaustive list of all responsibilities, duties and skills required of personnel so classified.

Pay and Benefits*:

Pay Range:

$72,600.00 - $120,600.00

Benefits:

Shirley Ryan AbilityLab offers a comprehensive benefits program that is competitive with our industry peers in our geographic locations:https://www.sralab.org/benefits

*Benefits and benefits' eligibility can vary by position. Actual compensation will be determined by equity and qualifications of the role.

Equal Employment Opportunity Employer

Shirley Ryan AbilityLab is an Equal Employment Opportunity Employer. All applicants will be afforded equal employment opportunity without discrimination because of race, color, religion, sex, marital status, national origin or ancestry, citizenship status, age, disability, sexual orientation, gender identity, genetic information, military status, order of protection status, unfavorable discharge from military service, or any other characteristics protected by law.

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Shirley Ryan AbilityLab is an Affirmative Action Employer as required by law.