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Junior Data Engineering Jobs in Chicago, IL (NOW HIRING)

RB Global Inc.

Staff Data Scientist

Westchester, IL · On-site

$100 - $140/hr

Perform feature engineering, data validation, and quality assurance across large, complex datasets ... Mentor junior data scientists and analysts, and contribute to best practices across the data ...

Heidrick & Struggles

Senior Data Engineer

Chicago, IL · On-site

$109K - $148K/yr

As a senior member of the data engineering team, you will own complex data solutions, drive best practices, and mentor junior engineers while ensuring our data platform is scalable, governed, and ...

Heidrick & Struggles

Senior Data Engineer

Chicago, IL

$109K - $148K/yr

As a senior member of the data engineering team, you will own complex data solutions, drive best practices, and mentor junior engineers while ensuring our data platform is scalable, governed, and ...

Ritchie Bros.

Staff Data Scientist

Westchester, IL · On-site

Perform feature engineering, data validation, and quality assurance across large, complex datasets ... Mentor junior data scientists and analysts, and contribute to best practices across the data ...

Noblesoft Technologies

SAP BODS Consultant

Chicago, IL · On-site

Mentor and train junior data engineers and other team members on best practices and emerging technologies in data engineering. * Building and managing DevOps & DataOps CI/CD pipelines and automated ...

Akuna Capital

Software Engineer - Data Engineering

Chicago, IL · On-site

$118K - $141K/yr

... junior engineers in software and data engineering best practices • Produce clean, well-tested, and documented code with a clear design to support mission critical applications • Build automated ...

Akuna Capital

Software Engineer - Data Engineering

Chicago, IL · On-site

$118K - $141K/yr

... junior engineers in software and data engineering best practices • Produce clean, well-tested, and documented code with a clear design to support mission critical applications • Build automated ...

Paul Hastings

Senior Data Engineer

Chicago, IL

$194K/yr

Mentor junior data engineers and promote best practices in CI/CD, version control, and release management. Proficiencies: * Advanced proficiency inAzure Data Factory,Azure Data Lake Storage (Gen2 ...

Addison Group

Sr. Data Scientist

Chicago, IL · Remote

$85 - $100/hr

Collaborate with cross-functional teams, including engineering, data, and business stakeholders ... Mentor junior data scientists by providing technical guidance, reviewing work, and fostering their ...

Kemper

Data Quality Engineer

Downers Grove, IL · Remote

$114K - $137K/yr

Mentor junior team members and promote best practices in data quality engineering and testing. Position Qualifications: Required Skills and Experience * Bachelor's degree in Computer Science ...

Kemper

Data Quality Engineer

Chicago, IL · Remote

$118K - $141K/yr

Mentor junior team members and promote best practices in data quality engineering and testing. Position Qualifications: Required Skills and Experience * Bachelor's degree in Computer Science ...

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All JobsData Engineering JobsJunior Data Engineering JobsJunior Data Engineering Jobs in Chicago, IL

Junior Data Engineering information

See Chicago, IL salary details

$34.5K

$74K

$112.8K

How much do junior data engineering jobs pay per year?

As of Aug 21, 2026, the average yearly pay for junior data engineering in Chicago, IL is $73,964.00, according to ZipRecruiter salary data. Most workers in this role earn between $50,000.00 and $82,400.00 per year, depending on experience, location, and employer.

What does a junior data engineer do?

A Junior Data Engineer typically assists in designing, building, and maintaining data pipelines and databases to support analytics and business needs. They work with large datasets, ensuring data is collected, stored, and processed efficiently and accurately. Responsibilities often include data cleaning, ETL (Extract, Transform, Load) processes, and collaborating with data analysts and other engineers. Junior Data Engineers are usually early in their careers and work under the guidance of more experienced data engineers while developing their technical and problem-solving skills.

What are the key skills and qualifications needed to thrive as a junior data engineer?

To thrive as a Junior Data Engineer, you need a solid understanding of data structures, SQL, and programming languages like Python or Java, often supported by a degree in computer science or a related field. Familiarity with ETL tools, cloud platforms (such as AWS or Azure), and data warehousing solutions is typically required. Strong problem-solving abilities, attention to detail, and effective communication help you excel in team environments and manage complex data workflows. These skills ensure you can reliably build, maintain, and optimize data pipelines that support organizational decision-making.

What are some typical challenges a junior data engineer may face when starting out, and how can they overcome them?

As a Junior Data Engineer, one common challenge is adapting to complex data infrastructure and unfamiliar tools or frameworks. You may also find it challenging to ensure data quality and consistency while working with large datasets. Collaborating closely with senior engineers and asking questions is key to overcoming these hurdles. Taking advantage of onboarding resources, documentation, and code reviews will help you learn best practices and improve your skills quickly. Embracing continuous learning and seeking feedback will set you up for long-term growth in data engineering.

What is the difference between Junior Data Engineering vs Data Analyst?

AspectJunior Data EngineeringData Analyst
Required SkillsBasic SQL, Python, data pipeline knowledgeData visualization, SQL, Excel
CertificationsEntry-level certifications in data engineering or related fieldsCertifications in data analysis or visualization tools
Work EnvironmentData engineering teams, IT departmentsBusiness units, marketing, finance teams
Industry UsageBuilding and maintaining data pipelines and infrastructureInterpreting data, creating reports and dashboards

Junior Data Engineering focuses on developing and maintaining data pipelines and infrastructure, requiring skills in SQL and Python. Data Analysts interpret data and create reports, often using visualization tools. While both roles work with data, Junior Data Engineers handle data flow and storage, whereas Data Analysts focus on data interpretation and insights.

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

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

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

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

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

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

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

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

Junior Data Engineering jobs near you
Infographic showing various Junior Data Engineering job openings in Chicago, IL as of August 2026, with employment types broken down into 17% Internship, 50% Full Time, and 33% Contract. Highlights an 83% In-person, and 17% Remote job distribution, with an average salary of $73,964 per year, or $35.6 per hour.

Jr. Data Engineer - Databricks / PySpark / Power BI

Aptino

Lincolnshire, IL • On-site

$120K - $144K/yr

Other

Posted yesterday

New

Job description

Role: Jr. Data Engineer – Databricks / PySpark / Power BI
Location: Lincolnshire, IL – Onsite
Duration: 12 Months

Job Overview:

We are seeking an experienced Data Engineer to take ownership of enterprise data engineering, analytics, and production support initiatives. This is a hands-on technical role requiring strong expertise in SQL, Databricks, PySpark, and Power BI, along with the ability to work directly with client stakeholders and coordinate distributed/offshore engineering teams.

The ideal candidate will be responsible for the full lifecycle of data solutions—from requirements and architecture through development, production support, troubleshooting, optimization, and continuous improvement.

Key Responsibilities:
  • Design, develop, enhance, and support enterprise-scale data pipelines and data-driven business solutions.
  • Build and optimize robust ETL/ELT pipelines using Databricks, PySpark, and advanced SQL.
  • Develop efficient data models and perform SQL query optimization, performance tuning, and troubleshooting.
  • Develop and maintain Power BI dashboards, reports, semantic/data models, and analytics solutions, including DAX.
  • Translate business and functional requirements into scalable technical data solutions.
  • Partner directly with client stakeholders to understand requirements, communicate technical solutions, and manage expectations.
  • Take ownership of production support, including incident investigation, troubleshooting, problem resolution, and root cause analysis (RCA).
  • Drive continuous improvement initiatives focused on performance, reliability, automation, scalability, and operational efficiency.
  • Coordinate with offshore development/support teams, monitor delivery, and ensure solutions meet quality and timeline expectations.
  • Identify opportunities to automate repetitive processes and improve development and operational workflows.
  • Support data platform enhancements, releases, and production deployments while maintaining platform stability.
  • Provide technical guidance and ensure end-to-end ownership of assigned data engineering initiatives.
Required Qualifications:
  • 5+ years of overall IT experience, with at least 4+ years in Data Engineering and Analytics.
  • Expert-level SQL skills, including query optimization, complex queries, data modeling, and performance tuning.
  • Strong hands-on experience with Databricks, preferably in a Google Cloud Platform environment; experience must be with non-Azure Databricks.
  • Strong development experience using PySpark for large-scale data processing and transformation.
  • Advanced Power BI experience, including DAX, dashboard development, reporting, and data modeling.
  • Proven experience designing, developing, and supporting large-scale ETL/ELT pipelines and enterprise data platforms.
  • Hands-on experience with production support, incident management, troubleshooting, and RCA.
  • Strong client-facing communication and stakeholder management skills.
  • Experience working in an onsite/offshore delivery model and coordinating distributed engineering teams.
  • Strong analytical and problem-solving skills with the ability to bridge business requirements and technical implementation.
Preferred Skills:
  • Google BigQuery
  • Python
  • Delta Lake
  • Data Lakehouse architecture
  • CI/CD
  • DataOps
  • Data pipeline automation and performance optimization

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