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Data Engineer Jobs in Park Ridge, IL (NOW HIRING)

CoSourcing Partners

GCP Data Engineer

Chicago, IL · On-site

$118K - $141K/yr

GCP Data Engineer Duration: 6 months Contract to hire Location: Chicago is the preferred location, but open to candidates from anywhere in the U.S. Role Overview We are seeking a highly skilled GCP ...

Next Step Systems

Data Engineer, Trading

Chicago, IL · On-site

$118K - $141K/yr

Data Engineer, Trading, Chicago, IL A proprietary trading firm is seeking a Data Engineer with Trading experience to join its Data Infrastructure team, to help improve and extend the data platform.

Deloitte

Databricks Data Engineer

Chicago, IL

$118K - $141K/yr

As a Databricks Data Engineer, you will support the design, build, and optimization of cloud-based data engineering solutions that enable large-scale transformation. You will work with business and ...

Jenner & Block

Enterprise Data Engineer

Chicago, IL

$118K - $141K/yr

POSTION SUMMARY Jenner & Block is seeking an experienced Enterprise Data Engineer to join our Information Technology team. In this role, you will design, build, and maintain the data pipelines and ...

Contact Government Services, LLC

Data Engineer

Chicago, IL · On-site

$118K - $141K/yr

Data Engineer Employment Type: Full-Time, Mid-level Department: Business Intelligence CGS is seeking a passionate and driven Data Engineer to support a rapidly growing Data Analytics and Business ...

NEWITY

Data Engineer

Chicago, IL · On-site

$117K - $141K/yr

Work with Product, Engineering, Operations, Sales, and Compliance so data solutions actually fit the downstream use case * Write the runbooks and documentation that on-call teammates and stakeholders ...

Contact Government Services, LLC

Data Engineer

Chicago, IL · On-site

$118K - $141K/yr

Data Engineer Employment Type: Full-Time, Mid-level Department: Business Intelligence CGS is seeking a passionate and driven Data Engineer to support a rapidly growing Data Analytics and Business ...

Contact Government Services LLC

Data Engineer

Chicago, IL

$118K - $141K/yr

Data Engineer Employment Type: Full-Time, Mid-level CGS is seeking a passionate and driven Data Engineer to support a rapidly growing Data Analytics and Business Intelligence platform focused on ...

AceStack LLC

Snowflake Data Engineer

Chicago, IL

$118K - $141K/yr

Snowflake Data Engineer Location: Chicago, IL (Local Prefers) Contract Experience Level 8+ years in Data Engineering, with a proven track record of leading large-scale data modernization or ...

Diverse Lynx

Data Engineer - Lead

Deerfield, IL

$85/hr

Data Engineer - Lead Location: Irvine, CA - onsite Duration: 6 months Rate- $85/hr C2C Data engineering delivery- POD level; Skills- pipeline design, performance tuning (Databricks, Spark, PySpark ...

Equiliem

Data Engineer

Chicago, IL

$118K - $141K/yr

Data Engineer hybrid model Location: 311 S Wacker Dr #1600, Chicago, IL & Ann Arbor, MI. Job type: 9 Months Contract Exp Level: Min 8+ Years. * Design, develop, and maintain database structures and ...

CVS Health

Data Engineer

Downers Grove, IL · On-site +1

$113K - $158K/yr

Data Engineer to analyze data engineering problems and develop, build and manage large-scale data structures, pipelines and efficient Extract/Load/Transform (ETL) workflows to address complex ...

Nava Software Solutions

Sr. Data Engineer

Chicago, IL · Hybrid

$118K - $141K/yr

Details: Sr. Data Engineer Location: Chicago, IL (Hybrid at least 2 days a week) Duration: 6-12 months Key Responsibilities and Essential Functions: * Design, build, and support durable data ...

Rush University Medical Center

Data Engineer

Chicago, IL

$46.07 - $68.64/hr

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 ...

Capital One

Lead Data Engineer

Chicago, IL

$118K - $141K/yr

Lead Data Engineer Do you love building and pioneering in the technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery ...

CVS Health

Data Engineer

Downers Grove, IL · On-site +1

$113K - $158K/yr

Data Engineer to analyze data engineering problems and develop, build and manage large-scale data structures, pipelines and efficient Extract/Load/Transform (ETL) workflows to address complex ...

New

Green Thumb

Data Engineer

Chicago, IL · Hybrid

$118K - $141K/yr

You'll design and maintain the pipelines, infrastructure, and systems that make clean, reliable data possible so that analysts, engineers, and business stakeholders can trust what they're looking at.

NAVA Software Solutions

Sr. Data Engineer

Chicago, IL · On-site

$118K - $141K/yr

Details: Sr. Data Engineer Location: Chicago, IL (Hybrid at least 2 days a week) Duration: 6-12 months Key Responsibilities and Essential Functions: * Design, build, and support durable data ...

CVS Health

Data Engineer

Chicago, IL · On-site +1

$113K - $158K/yr

Data Engineer to analyze data engineering problems and develop, build and manage large-scale data structures, pipelines and efficient Extract/Load/Transform (ETL) workflows to address complex ...

New

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Showing results 1-20

All JobsData Engineer JobsData Engineer Jobs in Park Ridge, IL

Data Engineer information

See Park Ridge, IL salary details

$43.8K

$127.6K

$174.7K

How much do data engineer jobs pay per year?

As of Jun 22, 2026, the average yearly pay for data engineer in Park Ridge, IL is $127,641.00, according to ZipRecruiter salary data. Most workers in this role earn between $112,700.00 and $135,300.00 per year, depending on experience, location, and employer.

What is the difference between Data Engineer vs Data Scientist?

AspectData EngineerData Scientist
Primary FocusBuilding and maintaining data pipelines and infrastructureAnalyzing data to extract insights and create models
SkillsSQL, ETL, programming (Python, Java), database managementStatistics, machine learning, data analysis, programming (Python, R)
Work EnvironmentData warehouses, cloud platforms, backend systemsData analysis environments, research labs, visualization tools
Common ToolsApache Spark, Hadoop, Airflow, SQLJupyter, RStudio, Tableau, scikit-learn

Data Engineers focus on creating and maintaining the infrastructure that allows data to be collected, stored, and processed efficiently. Data Scientists analyze this data to generate insights, build predictive models, and support decision-making. While their skills overlap, Data Engineers are more involved in data pipeline development, whereas Data Scientists focus on data analysis and modeling.

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

To thrive as a Data Engineer, you need a strong background in computer science, data modeling, and programming languages such as Python or Java, often coupled with a relevant degree. Familiarity with ETL tools, big data frameworks (like Hadoop or Spark), and cloud platforms (such as AWS or Azure) is typically required, along with certifications like AWS Certified Data Analytics. Strong problem-solving skills, attention to detail, and effective communication set exceptional data engineers apart. These skills and qualities are essential for building robust data pipelines, ensuring data quality, and supporting data-driven decision-making across organizations.

Are data engineers highly paid?

Data engineers are generally well-paid due to their specialized skills in designing and maintaining data infrastructure, with salaries often higher than many other IT roles. Compensation varies based on experience, location, and industry, but strong technical skills in programming, databases, and cloud platforms typically lead to higher earnings.

What Does a Data Engineer Do?

The job duties of a data engineer involve helping with the development of systems, software, and infrastructure used to process, store and analyze data. Your responsibilities in this career include working to install data management software. Your employer may expect you to perform maintenance and install updates to all software and systems that they use for data acquisition, management, and analysis. Data engineers also analyze existing data systems to find ways to improve efficiency and accessibility. You then suggest upgrades or changes based on your assessment.

What are Data Engineers?

Data Engineers are IT professionals who design, construct, install, and maintain large-scale processing systems and other infrastructure for collecting, storing, and analyzing data. They build and optimize data pipelines and architectures that allow organizations to efficiently access and use data for business insights. Data Engineers work closely with data scientists, analysts, and other stakeholders to ensure that data is reliable, accessible, and secure. Their responsibilities often include working with databases, cloud platforms, and big data tools.

How do Data Engineers typically collaborate with Data Scientists and Analysts within an organization?

Data Engineers play a crucial role in ensuring that Data Scientists and Analysts have reliable, well-structured data for their projects. This collaboration often involves building and maintaining data pipelines, optimizing data storage solutions, and troubleshooting data quality issues. Regular communication and agile teamwork are common, with Data Engineers frequently participating in meetings to understand analytical requirements and adjust data processes accordingly. By working closely together, these teams can quickly iterate on data models and deliver actionable insights to drive business decisions.

What does a data engineer actually do?

A data engineer designs, builds, and maintains the infrastructure and pipelines that enable organizations to collect, store, and process large volumes of data. They work with tools like SQL, Python, and cloud platforms to ensure data is accessible, reliable, and ready for analysis by data scientists and analysts.

Is a data engineer entry level?

Data engineering is typically an intermediate to senior role that requires experience with programming, databases, and data pipeline tools. Entry-level data engineering positions may be available for candidates with relevant internships or strong foundational skills in SQL, Python, or cloud platforms, but most roles expect some prior experience. Certifications or coursework in data management can also be beneficial for those starting out.

What engineer makes $500,000 a year?

Senior data engineers with extensive experience, advanced skills in big data tools, and leadership roles can earn salaries approaching or exceeding $500,000 annually, especially in high-cost-of-living areas or large tech companies. Such compensation often includes base salary, bonuses, and stock options. Achieving this level typically requires years of expertise and a strong track record in data architecture and engineering.
More about Data Engineer jobs
What are the most commonly searched types of Data Engineer jobs in Park Ridge, IL? The most popular types of Data Engineer jobs in Park Ridge, IL are:
What job categories do people searching Data Engineer jobs in Park Ridge, IL look for? The top searched job categories for Data Engineer jobs in Park Ridge, IL are:
What cities near Park Ridge, IL are hiring for Data Engineer jobs? Cities near Park Ridge, IL with the most Data Engineer job openings:
Data Engineer jobs near you
GCP Data Engineer

GCP Data Engineer

CoSourcing Partners

Chicago, IL • On-site

$118K - $141K/yr

Other

Posted 18 days ago

Job description

Job Title: GCP Data Engineer
Duration: 6 months Contract to hire
Location: Chicago is the preferred location, but open to candidates from anywhere in the U.S.
Role Overview
We are seeking a highly skilled GCP Data Engineer to design, develop, and optimize scalable data solutions on Google Cloud Platform (GCP). The ideal candidate will have strong expertise in building robust batch and streaming pipelines, implementing modern data architectures, and enabling reliable, high-quality data platforms for analytics, reporting, and machine learning use cases.
Key Responsibilities
Data Engineering & Pipeline Development
  • Design, build, and optimize scalable batch and real-time (streaming) data pipelines using GCPnative services.
  • Develop and maintain data ingestion frameworks leveraging tools such as Pub/Sub, Dataflow, and Cloud Storage.
  • Implement data transformation pipelines using BigQuery, dbt, and Python-based workflows.
  • Ensure efficient handling of large-scale structured and unstructured datasets. Data Modeling & Architecture
  • Design and implement high-performance data models for cloud-based data lakes, data warehouses, and analytics platforms.
  • Optimize data schemas and partitioning strategies in BigQuery for performance and cost efficiency.
  • Support modern architectures such as medallion (bronze/silver/gold) layers and lakehouse patterns.

Development & Coding
  • Write advanced SQL queries for transformation, validation, and analytics.
  • Develop scalable data processing logic using Python and/or Apache Beam.
  • Build reusable, modular, and maintainable code for data workflows.

Data Quality, Observability & Reliability
  • Implement and maintain data quality checks, validation rules, and anomaly detection frameworks.
  • Enable data observability through monitoring, logging, and alerting mechanisms.
  • Ensure highly reliable data pipelines with fault tolerance and error handling strategies.

ETL/ELT Modernization
  • Support migration and modernization efforts from legacy ETL tools (e.g., Talend) to GCP-native ELT frameworks (dbt).
  • Optimize existing pipelines for performance, scalability, and maintainability in cloud environments.
  • Drive adoption of ELT best practices using BigQuery as the compute engine.

Collaboration & Stakeholder Engagement
  • Collaborate with data architects, business analysts, and machine learning teams to deliver trusted datasets.
  • Translate business requirements into scalable data solutions.
  • Provide technical guidance and support for downstream analytics and reporting use cases.

Best Practices & Governance
  • Drive adoption of best practices in cloud data engineering, CI/CD, and DevOps.
  • Implement secure data access controls using IAM roles, policies, and governance frameworks.
  • Follow standards for code quality, version control (Git), and automated deployments.

Required Qualifications
  • Bachelor's or Master's degree in Computer Science, Engineering, or related field.
  • 4+ years of experience in data engineering or data platform development.
  • Hands-on experience with Google Cloud Platform (GCP) services:
  • BigQuery
  • Dataflow
  • Pub/Sub
  • Cloud Storage
  • Strong proficiency in SQL and Python.
  • Experience with dbt (Data Build Tool) or similar ELT frameworks.
  • Experience building batch and streaming data pipelines.

Preferred Skills
  • Experience with Apache Beam or Spark.
  • Familiarity with Talend or other ETL tools and migration to cloud-native solutions.
  • Knowledge of data lakehouse architectures and modern data stack.
  • Experience with CI/CD tools (e.g., GitHub Actions, Cloud Build, Jenkins).
  • Understanding of data security, governance, and compliance standards.
  • Exposure to machine learning data pipelines and feature engineering.

Key Competencies
  • Strong problem-solving and analytical skills
  • Ability to work in cross-functional teams
  • Excellent communication and documentation skills
  • Focus on performance optimization and scalability
  • Attention to data quality and reliability

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