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Data Engineer Entry Level Jobs in Chicago, IL (NOW HIRING)

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Data Engineer Entry Level information

See Chicago, IL salary details

$45.9K

$133.7K

$183K

How much do data engineer entry level jobs pay per year?

As of Aug 17, 2026, the average yearly pay for data engineer entry level in Chicago, IL is $133,732.00, according to ZipRecruiter salary data. Most workers in this role earn between $118,000.00 and $141,800.00 per year, depending on experience, location, and employer.

What does a data engineer entry level do?

An entry-level data engineer is responsible for designing, building, and maintaining systems that allow organizations to collect, store, and analyze large amounts of data. They typically work with databases, data pipelines, and cloud platforms to ensure data is accessible and reliable for analysis. Entry-level data engineers often assist with cleaning and transforming raw data, automating data workflows, and supporting data scientists and analysts. They also learn best practices in data security and performance optimization as they gain experience.

What are some typical projects or tasks that entry-level data engineers work on during their first year?

As an entry-level data engineer, you can expect to work on tasks such as building and maintaining data pipelines, cleaning and transforming raw data, and supporting the integration of different data sources. You'll often collaborate with data analysts and more senior engineers to ensure data is accurate, accessible, and well-documented. Early projects might include automating data extraction processes, setting up basic ETL (Extract, Transform, Load) workflows, or optimizing database queries. These foundational responsibilities help build the technical and teamwork skills essential for career growth in data engineering.

What are the key skills and qualifications needed to thrive as an entry level data engineer, and why are they important?

To thrive as an Entry Level Data Engineer, you need foundational knowledge in programming (such as Python or SQL), data structures, and database management, often supported by a degree in computer science or a related field. Familiarity with ETL tools, cloud platforms (like AWS or Azure), and version control systems is typically expected. Strong problem-solving skills, attention to detail, and effective communication help you collaborate with teams and adapt to evolving data needs. These skills ensure accurate data processing, efficient pipeline development, and successful integration within data-driven organizations.

What is the difference between Data Engineer Entry Level vs Data Analyst Entry Level?

AspectData Engineer Entry LevelData Analyst Entry Level
Required CredentialsBachelor's in CS, IT, or related field; some certifications (e.g., Google Cloud, AWS)Bachelor's in Statistics, Math, or related field; certifications like Microsoft Data Analyst
Work EnvironmentFocus on building data pipelines, databases, and infrastructureFocus on interpreting data, creating reports, and visualizations
Employer & Industry UsageTech companies, finance, healthcare, where data infrastructure is keyBusiness intelligence, marketing, finance, and consulting firms

While both roles involve working with data, Data Engineer Entry Level focuses on developing and maintaining data infrastructure, whereas Data Analyst Entry Level emphasizes analyzing data to generate insights. Both roles require strong technical skills and are essential in data-driven organizations.

Can I get a data engineer entry level job with no experience?

Entry-level data engineering positions typically require some knowledge of programming languages like Python or SQL, as well as familiarity with data tools and platforms such as Hadoop or Spark. While prior work experience is not always mandatory, having relevant coursework, certifications, or internships can improve your chances of securing an entry-level role.

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

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

What job categories do people searching Data Engineer Entry Level jobs in Chicago, IL look for?

The top searched job categories for Data Engineer Entry Level jobs in Chicago, IL are:

What cities near Chicago, IL are hiring for Data Engineer Entry Level jobs?

Cities near Chicago, IL with the most Data Engineer Entry Level job openings:

Infographic showing various Data Engineer Entry Level job openings in Chicago, IL as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $133,732 per year, or $64.3 per hour.

Tax Innovation - Data Engineer - Senior Associate

Pwc

Chicago, IL

$77K - $214K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 5 days ago


PwC rating

8.3

Company rating: 8.3 out of 10

Based on 76 frontline employees who took The Breakroom Quiz

26th of 72 rated business consultants


Job description

Industry/Sector

Not Applicable

Specialism

Data Engineering

Management Level

Senior Associate

Job Description & Summary

The Opportunity
As a Tax Innovation - Data Engineer - Senior Associate, you will play a pivotal role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth. Within our Tax practice, you will focus on designing and building data infrastructure and systems to facilitate efficient data processing and analysis. You will be responsible for developing and implementing data pipelines, data integration, and data transformation solutions.
As a Senior Associate, you will leverage your skills to build meaningful client connections and learn how to manage and inspire others. Navigating increasingly complex situations, you will grow your personal brand and deepen your technical skills. You are expected to anticipate the needs of your teams and clients, delivering quality solutions. Embracing increased ambiguity, you will be comfortable when the path forward isn't clear, using these moments as opportunities to grow.
In this role, you will utilize a broad range of tools and methodologies to generate new ideas and solve problems. You will interpret data to inform insights and recommendations, upholding professional and technical standards. This position offers a unique opportunity to develop a deeper understanding of the business context and how it is evolving.
Responsibilities
- Designing and developing data infrastructure and systems to facilitate efficient data processing and analysis
- Implementing data pipelines, integration, and transformation solutions to support client needs
- Utilizing Azure Data Factory and Databricks Unified Data Analytics Platform for data engineering tasks
- Developing data architecture and modeling strategies to optimize data flow and storage
- Applying database management and security best practices to maintain data integrity
- Building and maintaining data lakes and warehouses, including Snowflake Data Warehouse
- Conducting data validation and quality checks to support accurate insights generation
- Collaborating with clients to understand their data requirements and deliver tailored solutions
- Leveraging analytical thinking and creativity to solve complex data challenges
- Engaging in performance tuning and query optimization to enhance system efficiency
- Supporting the development of data strategy and governance frameworks to align with business objectives
What You Must Have
- At least a Bachelor's degree
- At least 3 years of experience
What Sets You Apart
- Preference for at least one of the following fields of study: Analytics/Data Science, Business Administration/Management, Computer Science/Information Systems, Economics, Engineering, Finance, Mathematics/Statistics, Operations/Supply Chain
- Demonstrating proficiency in Azure Data Factory and Microsoft Azure Databricks
- Utilizing advanced skills in data modeling and data pipeline development
- Excelling in data architecture development and database management systems
- Implementing data anonymization and database security best practices
- Leveraging experience with Snowflake Data Warehouse and Databricks Unified Data Analytics Platform
- Applying analytical thinking and creativity to solve complex data engineering challenges

Travel Requirements

Up to 20%

Job Posting End Date

The salary range for this position is: $77,000 - $214,000. Actual compensation within the range will be dependent upon the individual's skills, experience, qualifications and location, and applicable employment laws. All hired individuals are eligible for an annual discretionary bonus. PwC offers a wide range of benefits, including medical, dental, vision, 401k, holiday pay, vacation, personal and family sick leave, and more. To view our benefits at a glance, please visit the following link: https://pwc.to/benefits-at-a-glanceAs PwC is anequal opportunity employer, all qualified applicants will receive consideration for employment at PwC without regard to race; color; religion; national origin; sex (including pregnancy, sexual orientation, and gender identity); age; disability; genetic information (including family medical history); veteran, marital, or citizenship status; or, any other status protected by law.PwC does not intend to hire experienced or entry level job seekers who will need, now or in the future, PwC sponsorship through the H-1B lottery, except as set forth within the following policy: https://pwc.to/H-1B-Lottery-Policy.Learn more about how we work: https://pwc.to/how-we-workFor only those qualified applicants that are impacted by the Los Angeles County Fair Chance Ordinance for Employers, the Los Angeles' Fair Chance Initiative for Hiring Ordinance, the San Francisco Fair Chance Ordinance, San Diego County Fair Chance Ordinance, and the California Fair Chance Act, where applicable, arrest or conviction records will be considered for Employment in accordance with these laws. At PwC, we recognize that conviction records may have a direct, adverse, and negative relationship to responsibilities such as accessing sensitive company or customer information, handling proprietary assets, or collaborating closely with team members. We evaluate these factors thoughtfully to establish a secure and trusted workplace for all.

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