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Data Processing Jobs in Illinois (NOW HIRING)

AI Data Engineer

Moline, IL · On-site

$103K - $124K/yr

Design, develop, and manage data pipelines to handle and process large datasets with a focus on scalability and efficiency. Langchain Integration: Utilize Langchain to build and optimize AI workflows ...

Data Engineer

Chicago, IL · On-site

$118K - $141K/yr

Responsibilities : • Architect, develop and deploy our Big Data environment (Kafka, Hadoop, Dremio, etc.) • Build, deploy, and monitor our data processing pipelines (Java, Python, Spark, Flink ...

Data Engineer

Chicago, IL · On-site

$118K - $141K/yr

Support ETL/ELT processes and collaborate with data engineering teams. * Collaboration & Leadership: Partner with application developers, data engineers, BI teams, and stakeholders to understand data ...

Develop, maintain, and enhance complex and diverse software algorithms (e.g. processing-intensive analytics, novel process development, manipulation of large data sets). * Research analysis products ...

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 ...

This is an exciting opportunity for students or recent graduates who are passionate about data processing, analytics, and AI-driven insights. You will work on real-world projects, helping to ...

Data Engineer

Chicago, IL · Hybrid

$118K - $141K/yr

Ingest, store, process, and analyze large datasets efficiently, ensuring data is always accessible and accurate for downstream consumers * Design and maintain scalable data infrastructure and data ...

Data Engineer

Chicago, IL · On-site

$95K - $115K/yr

Ingest, store, process, and analyze large datasets efficiently, ensuring data is always accessible andaccuratefor downstream consumers * Design andmaintainscalable data infrastructure and data models ...

In data engineering at PwC, you will focus on designing and building data infrastructure and systems to enable efficient data processing and analysis. You will be responsible for developing and ...

In data engineering at PwC, you will focus on designing and building data infrastructure and systems to enable efficient data processing and analysis. You will be responsible for developing and ...

Data Engineer

Chicago, IL · On-site

$95K - $115K/yr

Ingest, store, process, and analyze large datasets efficiently, ensuring data is always accessible and accurate for downstream consumers * Design and maintain scalable data infrastructure and data ...

Azure Data Engineer

Chicago, IL · On-site

$118K - $141K/yr

Design and implement scalable ETL/ELT pipelines using Azure Data Factory (ADF). · Big Data Processing: Build high-performance, distributed data transformation workloads via Azure Databricks and ...

New

Senior Data AI Engineer

Chicago, IL · On-site

$118K - $141K/yr

Researches, identifies and implements process improvements that address complex technology gaps ... Strong SQL and data analytical skills; experience building data marts and feature datasets for data ...

Data Engineer

Chicago, IL · On-site

$175K - $225K/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

$175K - $225K/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 ...

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Data Processing information

See Illinois salary details

$11

$19

$33

How much do data processing jobs pay per hour?

As of Jul 13, 2026, the average hourly pay for data processing in Illinois is $19.64, according to ZipRecruiter salary data. Most workers in this role earn between $15.62 and $21.68 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Data Processing position, and why are they important?

To thrive in Data Processing, you need strong analytical abilities, attention to detail, and proficiency with spreadsheets and database management, often supported by an associate's degree or relevant experience. Familiarity with tools like Microsoft Excel, SQL, or data entry software, as well as certifications such as Certified Data Processor (CDP), are frequently expected. Strong organizational skills, time management, and the ability to troubleshoot problems efficiently are valued soft skills. These competencies are crucial for ensuring data accuracy, meeting deadlines, and supporting smooth information operations within an organization.

What is a data processing job role?

A data processing job involves collecting, organizing, and converting raw data into a usable format for analysis or reporting. It often requires skills in data management tools, attention to detail, and knowledge of data formats and software such as Excel, SQL, or specialized processing programs.

What are the typical daily responsibilities of someone working in Data Processing?

A typical day for a Data Processing professional involves entering, validating, and updating records in databases or spreadsheets to ensure data integrity. You may also be responsible for generating reports, cleaning large data sets, and identifying discrepancies or errors for correction. Collaboration with team members or departments is common to clarify data requirements and resolve issues. Staying organized and attentive to detail is essential because the quality of processed data can impact decision-making across the organization.

What is a Data Processing job?

A Data Processing job involves collecting, organizing, and managing data to ensure accuracy and accessibility. Professionals in this role use software tools to input, clean, analyze, and process data for businesses or organizations. They may also generate reports and automate workflows to streamline data handling. Strong attention to detail and proficiency in data management tools are essential for success in this field.

Is AI replacing data entry jobs?

AI is automating many data entry tasks by using machine learning and optical character recognition, which can increase efficiency and reduce manual labor. However, data processing jobs still require human oversight for complex or unstructured data, and roles involving data validation, analysis, and management remain essential. Professionals in data processing should develop skills in AI tools and data management to stay relevant.

What is the highest paying job in data?

In data-related fields, roles such as Data Science Director, Chief Data Officer, or Senior Data Architect tend to have the highest salaries, often exceeding six figures annually. These positions typically require advanced skills in data analysis, machine learning, and leadership, along with extensive experience and relevant certifications.
What are the most commonly searched types of Data Processing jobs in Illinois? The most popular types of Data Processing jobs in Illinois are:
What cities in Illinois are hiring for Data Processing jobs? Cities in Illinois with the most Data Processing job openings:
Infographic showing various Data Processing job openings in Illinois as of July 2026, with employment types broken down into 1% As Needed, 87% Full Time, 10% Part Time, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $40,847 per year, or $19.6 per hour.
AI Data Engineer

AI Data Engineer

Instant Serve LLC

Moline, IL • On-site

$103K - $124K/yr

Other

Re-posted 2 days ago


Job description

For more details contact at Ella.s@iserveworld.com

Job Title: AI Data Engineer

Location: Moline,IL

Pay Rate:USD$60.00 $65.00 /hr.with benefits

Key Responsibilities

Data Engineering: Design, develop, and manage data pipelines to handle and process large datasets with a focus on scalability and efficiency.

Langchain Integration: Utilize Langchain to build and optimize AI workflows, automate processes, and enhance AI model capabilities with data-driven features.

Cloud Data Infrastructure: Manage and scale data infrastructure on AWS, using services such as S3, EC2, Lambda, Redshift, and others.

SQL & Database Expertise: Write complex SQL queries for data extraction, transformation, and analysis. Optimize database performance and ensure data integrity.

Collaboration: Work closely with Data Scientists, AI Engineers, and other stakeholders to ensure data is properly structured for machine learning models and other analytics use cases.

Data Quality & Governance: Monitor data quality, create processes for error handling, and ensure compliance with data privacy regulations and best practices.

Performance Optimization: Continuously optimize and fine-tune data processing pipelines and database queries for better performance and scalability.

Documentation: Maintain detailed documentation on the architecture, data processes, and code to ensure smooth collaboration and knowledge transfer.

Requirements

3+ years of experience as a Data Engineer, with a focus on AI or machine learning data pipelines.

Hands-on experience with Langchain for building and optimizing AI workflows and automation.

Strong experience with large-scale data management, including working with distributed systems and processing massive datasets.

Proficient in SQL and experience with relational databases (e.g., PostgreSQL, MySQL, SQL Server) and NoSQL databases.

Extensive experience with AWS, including services like S3, EC2, Lambda, Redshift, and RDS.

What are the 3-4 non-negotiable requirements of this position?
Experience: 3+ years of experience as a Data Engineer, with a focus on AI or machine learning data pipelines. Hands-on experience with Langchain for building and optimizing AI workflows and automation. Strong experience with large-scale data management, including working with distributed systems and processing massive datasets. Proficient in SQL and experience with relational databases (e.g., PostgreSQL, MySQL, SQL Server) and NoSQL databases. Extensive experience with AWS, including services like S3, EC2, Lambda, Redshift, and RDS. Technical Skills: Proficient in Python Strong understanding of database design, data modeling, and query optimization. Familiarity with data warehousing concepts and tools. Exerience working with data pipelines and workflow orchestration tools like Apache Airflow, or similar. Knowledge of AI and machine learning concepts, particularly around data preprocessing and feature engineering. Education: Bachelor's or Master's degree in Computer Science, Data Engineering, Artificial Intelligence, or a related field.

What are the nice-to-have skills?
Preferred Qualifications: Experience with Apache Spark, Kafka, or other big data technologies. Familiarity with containerization (Docker, Kubernetes) for deploying scalable data solutions. Knowledge of AI-specific data workflows, including data preparation for natural language processing, computer vision, or other AI applications.


InstantServe logo

About InstantServe

Sourced by ZipRecruiter

InstantServe provides a one-stop solution to all Healthcare, IT/Non-IT Staffing needs. Established in 2016, InstantServe is a strong workforce of over 100+ go-getters with a demonstrated background in IT/Non-IT service. We are a nationally certified SBE from the Department of Administration (State of PA). As a proud Minority Woman Owned Small Business Enterprise (M/WBE), InstantServe boasts of a strong team of professionals who have extensive experience catering to several Federal, Public, Commercial, and Healthcare Clients which includes 26 States and 46 government agencies. InstantServe is a client-centric organization that offers cost-effective and reliable solutions. Client satisfaction is sacrosanct! Our team strives to provide the best staffing and IT solutions to take your business to the next level.

Industry

Recruiting and staffing services

Company size

11 - 50 Employees

Headquarters location

Wayne, PA, US

Year founded

2016

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