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Data Processing Jobs in Chicago, IL (NOW HIRING)

NEWMARK

Staff Data Engineer

Chicago, IL · On-site

Expert-level SQL and strong proficiency in Python (Scala or Java a plus) for large-scale data processing and transformation. * Deep experience with cloud data platforms (e.g., Databricks, Snowflake ...

Google

Tax Data Systems and Process Analyst

Chicago, IL · On-site

Experience with data processing and management, including Relational Database Management Systems (RDBMS) such as Postgres or MySQL. * Experience with machine learning frameworks like TensorFlow and ...

Eliassen Group

Senior Data Engineer

Chicago, IL · On-site

$70 - $80/hr

Develop and optimize large-scale data processing solutions using Scala, Spark, and SQL on modern data platforms. * Build and operate trusted data pipelines across secure cloud environments such as ...

AArete

Healthcare Data Developer

Chicago, IL · On-site

$90K - $120K/yr

Develop SQL queries and Python scripts for data processing, transformation, validation, and automation * Implement and validate pricing logic based on business requirements * Perform functional ...

Allstate Insurance

Senior Data Engineer Con II

Chicago, IL · On-site

$109K - $148K/yr

Build and manage data processing workloads within modern lakehouse platforms, including Microsoft Fabric / OneLake (preferred). * Ensure data quality, reliability, and consistency by implementing ...

Tiger Analytics Inc.

Senior Data Engineer

Chicago, IL · On-site

$109K - $148K/yr

Build and maintain scalable data processing and transformation workflows using Databricks, Apache Spark, and SQL. * Develop and maintain Apache Airflow workflows for pipeline orchestration ...

Tiger Analytics Inc.

Senior Data Engineer

Chicago, IL

$109K - $148K/yr

Build and maintain scalable data processing and transformation workflows using Databricks, Apache Spark, and SQL. * Develop and maintain Apache Airflow workflows for pipeline orchestration ...

Tiger Analytics Inc.

Senior Data Engineer

Chicago, IL · Remote

$108K - $147K/yr

Build and maintain scalable data processing and transformation workflows using Databricks, Apache Spark, and SQL. * Develop and maintain Apache Airflow workflows for pipeline orchestration ...

WorkNovas LLC

Data & AI Architect

Chicago, IL · On-site

$65.75 - $84.50/hr

Experience with AI/ML data requirements including feature engineering, vector embeddings, retrieval augmented generation (RAG), and unstructured data processing. * Proficiency in SQL; working ...

Sonsoft Inc

Data Scientist (No H1B)

Chicago, IL

... js) or data processing (e.g., Spark, Stanford CoreNLP, gensim) Relational database and SQL skills Experience with cloud infrastructures Experience with tools and best practices for software ...

IMC

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 ...

Tredence Analytic

Data Engineer

Chicago, IL

$118K - $141K/yr

During various aspects of this process, you should collaborate with coworkers to ensure that your approach meets the needs of each project. To ensure success as a Data Engineer, you should ...

IMC

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

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How much do data processing jobs pay per hour?

As of Sep 2, 2026, the average hourly pay for data processing 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 data processing?

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.

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 are the key skills and qualifications needed to thrive in data processing, 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 do you do as a data processing?

A data processing professional collects, organizes, and analyzes data to ensure accuracy and usability. They use tools like spreadsheets, databases, and data management software to clean, transform, and prepare data for reporting or decision-making. Attention to detail and knowledge of data handling techniques are essential in this role.

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 most commonly searched types of Data Processing jobs in Chicago, IL?

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

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

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

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

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

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

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

Data Processing jobs near you
Infographic showing various Data Processing job openings in Chicago, IL as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $43,424 per year, or $20.9 per hour.

Staff Data Engineer

NEWMARK

Chicago, IL • On-site

Full-time

Medical, Dental, Vision

Re-posted 2 days ago

Newmark rating

9.2

Company rating: 9.2 out of 10

Based on 9 frontline employees who took The Breakroom Quiz

8th of 207 rated real estate companies

Job description

Responsibilities
  • Own and drive the technical architecture for complex, cross-team data initiatives spanning ingestion, transformation, storage, and serving layers.
  • Design, build, and maintain scalable, high-performance data pipelines and distributed data platforms in a cloud-native environment (Azure, AWS, or GCP).
  • Architect and lead enterprise Master Data Management (MDM), including golden records, entity resolution, data domains, reference and hierarchy management, and stewardship, to create trusted, authoritative data across the business.
  • Architect and integrate agentic AI and LLM-driven workflows (autonomous agents, RAG pipelines, AI copilots) into data platforms and pipelines to drive efficiency and new capabilities.
  • Build and support the data foundations for machine learning and AI, including feature stores, vector stores, embeddings, and ML/LLMOps pipelines.
  • Design and deliver backend data services and APIs (REST/GraphQL), and contribute across the stack to expose curated datasets to applications, analytics, and BI consumers.
  • Set engineering standards and best practices for data quality, modeling, testing, observability, and deployment across the organization, including responsible use of AI-assisted development tools.
  • Establish data governance, lineage, cataloging, and quality frameworks across the data estate.
  • Lead technical design reviews and provide architectural guidance to multiple engineering and data teams.
  • Partner with product, analytics, and engineering leadership to translate business strategy into scalable data roadmaps, including AI-driven capabilities.
  • Identify and resolve systemic performance, reliability, and scalability issues across the data stack.
  • Mentor and coach senior and mid-level engineers, raising the technical bar across the organization on data engineering, MDM, and AI practices.
  • Drive adoption of modern frameworks, tools, and engineering practices, including agentic AI and LLM tooling, to improve delivery velocity and platform resilience.
  • Maintain awareness of emerging technologies and industry trends, particularly in agentic AI, master data management, and modern data platforms, and assess their applicability to the business.

Qualifications
Basic Qualifications
  • Bachelor's degree in Computer Science, Engineering, MIS, or related field preferred.
  • 12+ years of experience in data engineering or software engineering, with demonstrated experience architecting data platforms and pipelines at scale.
  • Expert-level SQL and strong proficiency in Python (Scala or Java a plus) for large-scale data processing and transformation.
  • Deep experience with cloud data platforms (e.g., Databricks, Snowflake, Synapse, BigQuery, Redshift) and cloud-native architecture patterns.
  • Deep understanding of distributed systems, data modeling (dimensional, data vault, lakehouse), and ETL/ELT architecture.
  • Hands-on experience designing and implementing Master Data Management (MDM) solutions, including entity resolution, match/merge, golden records, and reference/hierarchy management (e.g., Informatica, Reltio, Profisee, or similar).
  • Hands-on experience building or integrating agentic AI systems, LLM-powered applications, RAG pipelines, or AI agent orchestration frameworks (e.g., LangChain, AutoGen, Semantic Kernel, MCP).
  • Experience building backend data services and APIs (REST/GraphQL), with comfort working across the full stack.
  • Strong background with both relational (SQL) and NoSQL data stores, plus data lake/lakehouse formats (Delta, Iceberg, Parquet).
  • Deep understanding of CI/CD pipelines, infrastructure as code, and DevOps/DataOps practices.
  • Proven track record of leading large-scale technical initiatives across multiple teams.
  • Demonstrated ability to mentor engineers and influence technical direction without direct reporting authority.

Preferred Qualifications
  • Experience with data governance, lineage, and cataloging tools (e.g., Unity Catalog, Microsoft Purview, Collibra, Alation).
  • Experience designing multi-agent systems, tool-calling architectures, or retrieval-augmented generation (RAG) pipelines.
  • Experience with event-driven architectures and streaming/real-time data processing (e.g., Kafka, Event Hubs, Kinesis, Flink, Spark Structured Streaming).
  • Experience building the data layer for ML/AI, including feature stores, vector databases, embeddings, and ML/LLMOps.
  • Familiarity with containerization and orchestration (Docker, Kubernetes) and workflow orchestration (Airflow, Dagster, dbt).
  • Prior experience in commercial real estate, fintech, or operations/transaction systems.
  • Track record of speaking, writing, or open-source contributions that demonstrate technical thought leadership, especially in applied AI or data.

Why Join Us?
  • Shape the technical direction of business-critical data platforms at enterprise scale, including master data management and next-generation agentic AI initiatives.
  • Be part of a high-impact team where ownership, innovation, and technical excellence drive success.
  • Competitive compensation, growth opportunities, and access to world-class engineering, data, and AI resources.
  • Collaborative Culture: Join a high-caliber team with deep expertise across data engineering, cloud, MDM, agentic AI, and distributed systems.
  • Growth & Learning: Access world-class learning resources and mentorship to advance your career.
  • Work-Life Balance: Flexible working hours and hybrid options.
  • Benefits: Comprehensive health, dental and vision insurance.

If you're passionate about architecting scalable data platforms, building trusted master data and agentic AI-driven solutions, and shaping engineering culture, we'd love to hear from you!
Apply now and help redefine the future of data and AI at scale!
Salary Language:
The expected base salary for this position ranges from $190,000 to $225,000 annually. The actual base salary will be determined on an individualized basis taking into account a wide range of factors including, but not limited to, relevant skills, experience, education, and, where applicable, licenses or certifications held. In addition to base salary and a competitive benefits package, this position may be eligible for additional types of compensation including discretionary bonuses and other short- and long-term incentives (e.g., deferred cash, equity, etc.).
Working Conditions: Normal working conditions with the absence of disagreeable elements.
Note: The statements herein are intended to describe the general nature and level of work being performed by employees, and are not to be construed as an exhaustive list of responsibilities, duties, and skills required of personnel so classified.
Newmark is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex including sexual orientation and gender identity, national origin, disability, protected Veteran Status, or any other characteristic protected by applicable federal, state, or local law.
About Us
Newmark Group, Inc. (Nasdaq: NMRK), together with its subsidiaries ("Newmark"), is a world leading commercial real estate advisor and service provider to large institutional investors and other owners, global corporations and other occupiers, and lenders. Built with purpose and driven by excellence, Newmark's comprehensive platform is uniquely tailored to provide superior outcomes to clients. For the twelve months ended June 30, 2026, Newmark generated revenues of more than $3.6 billion. As of June 30, 2026, Newmark and its business partners together operated from over 195 offices with more than 10,000 professionals across four continents. Learn more at nmrk.com or follow @newmark.
Discussion of Forward-Looking Statements about Newmark
Statements in this document regarding Newmark that are not historical facts are "forward-looking statements" that involve risks and uncertainties, which could cause actual results to differ from those contained in the forward-looking statements. These include statements about the Company's business, results, financial position, liquidity, and outlook, which may constitute forward-looking statements and are subject to the risk that the actual impact may differ, possibly materially, from what is currently expected. Except as required by law, Newmark undertakes no obligation to update any forward-looking statements. For a discussion of additional risks and uncertainties, which could cause actual results to differ from those contained in the forward-looking statements, see Newmark's Securities and Exchange Commission filings, including, but not limited to, the risk factors and Special Note on Forward-Looking Information set forth in these filings and any updates to such risk factors and Special Note on Forward-Looking Information contained in subsequent reports on Form 10-K, Form 10-Q or Form 8-K.

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