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Data Processor Jobs in Chicago, IL (NOW HIRING)

Data Engineer

Chicago, IL

$46.07 - $68.64/hr

Other information: • Bachelor's Degree. • 5 years of experience. • Strong background in cloud computing, software engineering and data processing. • Data management experience. • Experience ...

Data Architect

Chicago, IL · On-site

$65.75 - $84.50/hr

It requires deep technical expertise in data architecture, database design, ETL processes, reporting/analytics, big data, and cloud. The Data Architect should understand the system development life ...

Data Architect

Chicago, IL · On-site +1

$65.75 - $84.50/hr

It requires deep technical expertise in data architecture, database design, ETL processes, reporting/analytics, big data, and cloud. The Data Architect should understand the system development life ...

Data Engineer - Chicago, IL (Hybrid)

Chicago, IL · On-site

$118K - $141K/yr

Perform Develop and manage ETL processes using Python, PySpark, and SQL. * Work with Databricks for data processing. * Utilize AWS services like S3, CloudWatch, IAM, SNS, and Lambda. * Familiarity ...

Reporting to the Senior Director of Business Process and Data Ops, the ideal candidate combines strong analytical and problem-solving skills with an operational mindset, brings a solid understanding ...

Senior Data Analyst

Chicago, IL · On-site

$88K - $111K/yr

Skilled in data processing using Databricks or Jupyter Notebooks. * SQL : Proficient in complex data manipulation and retrieval. * AWS (S3) : Experience consuming and managing data in cloud storage.

Data Engineer

Chicago, IL

$118K - $141K/yr

Build, deploy, and monitor our data processing pipelines (Java, Python, Spark, Flink) * Collaborate with development teams on data modeling, data ingestion, and capacity planning * Work with users to ...

Data Engineer

Chicago, IL · On-site

$118K - $141K/yr

... processing. - Implement data quality checks, validation, and monitoring. - Enable machine learning workflows with clean, well-structured datasets. - Support analytics and reporting use cases ...

Data Engineer

Chicago, IL · On-site

$118K - $141K/yr

Key Responsibilities Data Engineering & Pipeline DevelopmentDesign, develop, and maintain end-to-end data pipelines in Databricks using Spark and Delta Lake Build and optimize ELT/ETL processes for ...

Showing results 21-40

Data Processor information

See Chicago, IL salary details

$12

$20

$35

How much do data processor jobs pay per hour?

As of Aug 22, 2026, the average hourly pay for data processor in Chicago, IL is $20.88, according to ZipRecruiter salary data. Most workers in this role earn between $16.59 and $23.03 per hour, depending on experience, location, and employer.

What is a data processor?

A data processor transfers, organizes, and processes personal data for a company. It is typically an entry-level job that serves as a starting point for a career as a data controller. As a data processor, your duties involve processing incoming documents, transferring analog documents into digital data, verifying the information in all documents, updating document formats, and creating detailed reports on company data use and management. Qualifications for this career include excellent computer skills and a bachelor’s degree in computer science or data management.

What are the key skills and qualifications needed to thrive as a data processor, and why are they important?

To thrive as a Data Processor, you need strong attention to detail, accuracy in data entry, and a high school diploma or equivalent. Familiarity with spreadsheet software (such as Microsoft Excel), database management systems, and sometimes data processing software is typically required. Excellent organizational skills, the ability to follow procedures, and effective time management make someone stand out in this role. These skills ensure data integrity, minimize errors, and support efficient information management within an organization.

What are some common challenges faced by data processors and how can they be addressed?

Data Processors often encounter challenges such as managing large volumes of data accurately and efficiently, dealing with inconsistent or incomplete data, and ensuring data privacy and compliance. To address these, it's important to develop strong attention to detail, become proficient with data processing software, and stay updated on relevant data protection regulations. Collaborating closely with data analysts and IT teams can also help resolve data issues and improve workflow efficiency.

What is the difference between Data Processor vs Data Entry Clerk?

AspectData ProcessorData Entry Clerk
Required CredentialsHigh school diploma; some roles may require basic certificationsHigh school diploma; no specialized certifications typically needed
Work EnvironmentOffice settings, data centers, or remote workOffice environments, often in administrative settings
Employer & Industry UsageBusinesses, government agencies, financial institutionsCorporations, healthcare, retail, administrative offices
Common Search & ComparisonOften compared for data handling and processing tasksCompared for data input and administrative support roles

While both roles involve handling data, Data Processors typically perform more complex data management and validation tasks, often requiring some technical skills. Data Entry Clerks focus on inputting data accurately and efficiently. Understanding these differences helps in choosing the right role based on skills and career goals.

How much does a data processor earn?

The average salary for a data processor typically ranges from $30,000 to $45,000 per year, depending on experience, location, and industry. Entry-level positions may start lower, while experienced data processors with specialized skills or certifications can earn higher wages. Many roles also offer benefits such as health insurance and paid time off.

What do you do as a data processor?

A data processor collects, organizes, and manages data to ensure accuracy and consistency. They often use software tools like spreadsheets or databases and may perform tasks such as data entry, validation, and updating records to support business operations.

What are the most commonly searched types of Data Processor jobs in Chicago, IL?

The most popular types of Data Processor jobs in Chicago, IL are:

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

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

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

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

What cities near Chicago, IL are hiring for Data Processor jobs?

Cities near Chicago, IL with the most Data Processor job openings:

Infographic showing various Data Processor job openings in Chicago, IL as of August 2026, with employment types broken down into 90% Full Time, 5% Part Time, and 5% Temporary. Highlights an 80% In-person, 10% Hybrid, and 10% Remote job distribution, with an average salary of $43,424 per year, or $20.9 per hour.

$46.07 - $68.64/hr

Full-time

Posted 19 days ago


Rush University Medical Center rating

8.1

Company rating: 8.1 out of 10

Based on 109 frontline employees who took The Breakroom Quiz

120th of 1,061 rated hospitals


Job description

Location: Chicago, Illinois

Business Unit: Rush Medical Center

Hospital: Rush University Medical Center

Department: Research Computing

Work Type: Full Time (Total FTE between 0. 9 and 1. 0) Remote 

Shift: Shift 1

Work Schedule: 8 Hr (8:00:00 AM - 5:00:00 PM)

Rush offers exceptional rewards and benefits learn more at our Rush benefits page (https://www.rush.edu/rush-careers/employee-benefits).

Pay Range: $46.07 - $68.64 per hour
Rush salaries are determined by many factors including, but not limited to, education, job-related experience and skills, as well as internal equity and industry specific market data. The pay range for each role reflects Rush’s anticipated wage or salary reasonably expected to be offered for the position. Offers may vary depending on the circumstances of each case.

Summary:
The Data Engineer is responsible for designing and implementing data pipelines for cloud projects. This position will require working with complex data sources and transforming it into something useful for analysts. Exemplifies the Rush mission, vision and values and acts in accordance with Rush policies and procedures.

Other information:
•Bachelor's Degree.
•5 years of experience.
•Strong background in cloud computing, software engineering and data processing.
•Data management experience.
•Experience in ETL Tools such as Pentaho, Talend, Informatica, Azure Data Factory, Apache Kafka and Apache Camel.
•Experience designing and implementing analysis solutions on Hadoop-based platforms such as Cloudera Hadoop, or Hortonworks Data Platform or Spark based platforms such as Databricks.
•Proficient in RDBMS such as Oracle, SQL Server, DB2, MySQL etc.
•Strong analytical and problem-solving skills.
•Strong verbal and written communication skills.
•Proficient programming skills in Python, SQL NoSQL, and Spark.
•Ability to manage multiple projects essential.
•Ability to work independently or in groups.
•Ability to prioritize time.
•Ability to adapt to a rapidly changing environment.
Preferred Job Qualifications:
Experience, education, licensure(s), specialized certification(s).
Cloud Certifications in AWS, Azure or GCP.
Physical Demands:
Competencies:
Disclaimer: The above is intended to describe the general content of and requirements for the performance of this job. It is not to be construed as an exhaustive statement of duties, responsibilities or requirements.
•Bachelor's Degree.
•5 years of experience.
•Strong background in cloud computing, software engineering and data processing.
•Data management experience.
•Experience in ETL Tools such as Pentaho, Talend, Informatica, Azure Data Factory, Apache Kafka and Apache Camel.
•Experience designing and implementing analysis solutions on Hadoop-based platforms such as Cloudera Hadoop, or Hortonworks Data Platform or Spark based platforms such as Databricks.
•Proficient in RDBMS such as Oracle, SQL Server, DB2, MySQL etc.
•Strong analytical and problem-solving skills.
•Strong verbal and written communication skills.
•Proficient programming skills in Python, SQL NoSQL, and Spark.
•Ability to manage multiple projects essential.
•Ability to work independently or in groups.
•Ability to prioritize time.
•Ability to adapt to a rapidly changing environment.
Preferred Job Qualifications:
Experience, education, licensure(s), specialized certification(s).
Cloud Certifications in AWS, Azure or GCP.
Physical Demands:
Competencies:
Disclaimer: The above is intended to describe the general content of and requirements for the performance of this job. It is not to be construed as an exhaustive statement of duties, responsibilities or requirements.
•Bachelor's Degree.
•5 years of experience.
•Strong background in cloud computing, software engineering and data processing.
•Data management experience.
•Experience in ETL Tools such as Pentaho, Talend, Informatica, Azure Data Factory, Apache Kafka and Apache Camel.
•Experience designing and implementing analysis solutions on Hadoop-based platforms such as Cloudera Hadoop, or Hortonworks Data Platform or Spark based platforms such as Databricks.
•Proficient in RDBMS such as Oracle, SQL Server, DB2, MySQL etc.
•Strong analytical and problem-solving skills.
•Strong verbal and written communication skills.
•Proficient programming skills in Python, SQL NoSQL, and Spark.
•Ability to manage multiple projects essential.
•Ability to work independently or in groups.
•Ability to prioritize time.
•Ability to adapt to a rapidly changing environment.
Preferred Job Qualifications:
Experience, education, licensure(s), specialized certification(s).
Cloud Certifications in AWS, Azure or GCP.
Physical Demands:
Competencies:
Disclaimer: The above is intended to describe the general content of and requirements for the performance of this job. It is not to be construed as an exhaustive statement of duties, responsibilities or requirements.

Responsibilities:
•Responsible for design, development and maintenance of data pipelines to enable data analysis and reporting.
•Builds, evolves and scales out infrastructure to ingest, process and extract meaning out data.
•Write complex SQL queries or python code to support analytics needs.
•Manage projects / processes, working independently with limited supervision
•Work with structured and unstructured data from a variety of data stores, such as data lakes, relational database management systems, and/or data warehouses.
•Combines, optimizes, and manages multiple big data sources.
•Builds data infrastructure and determines proper data formats to ensure data is ready for use.

Rush is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, and other legally protected characteristics.


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