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Data Analytics Engineer Jobs in Chicago, IL (NOW HIRING)

Steame LLC

Data Analytics Engineer - Chicago

Chicago, IL · On-site

$120K - $130K/yr

The Role As a Data Analytics Engineer at STEAMe, you will sit at the intersection of analytics, data engineering, and emerging AI-powered workflows. You'll be responsible for building reliable data ...

G&W Electric

Data Analytics Analyst II

Bolingbrook, IL · On-site

The Analyst II works closely with Data Analytics Developers and Engineers to ensure analytics solutions are based on trusted business definitions, consistent data standards, and clear reporting ...

Apex Informatics

Data Analyst

Chicago, IL · On-site

Cannot work with OPT or CPT Description NTRS Asset and Market Data team is looking for an experienced and versatile Data Analytics Engineer to help us build a Security Master System. In this role ...

Feastables

Senior Analytics Engineer

Chicago, IL · On-site

$130K - $160K/yr

Role Overview Feastables is building a modern CPG brand at scale, where data is critical to how the ... The Senior Analytics Engineer is responsible for building and maintaining the core data workflows ...

BMO Capital Markets

Manager, Data & Analytics

Chicago, IL · Hybrid

$74K - $138K/yr

Use SQL and Python (or similar programming languages) to extract, analyze, and visualize data. * Build scalable analytical solutions and automate recurring processes. * Collaborate with the Sr. ...

AllSTEM Connections

Data Analyst

Chicago, IL · On-site

$187K/yr

Senior Data & Analytics Engineer (Enterprise Intelligence) Role Overview We are seeking a high-caliber Senior Data & Analytics Engineer to serve as a Subject Matter Expert (SME) within our enterprise ...

Bank of Montreal

Manager, Data & Analytics

Chicago, IL · On-site

$74K - $138K/yr

Use SQL and Python (or similar programming languages) to extract, analyze, and visualize data. * Build scalable analytical solutions and automate recurring processes. * Collaborate with the Sr. ...

Traffic Tech

Analytics Engineer

Chicago, IL · On-site

The Analytics Engineer role involves working with internal customers to understand their data needs, developing data pipelines, and maintaining data quality to support business operations.

Traffic Tech Inc.

Analytics Engineer

Chicago, IL

ANALYTICS ENGINEER What the Job Entails: * Work with internal customers to understand their data ... Develop and maintain data pipelines to extract or ingest new data sources to a data warehouse ...

Traffic Tech Inc.

Analytics Engineer

Chicago, IL · On-site

ANALYTICS ENGINEER What the Job Entails: * Work with internal customers to understand their data ... Develop and maintain data pipelines to extract or ingest new data sources to a data warehouse ...

Traffic Tech Inc.

Analytics Engineer

Chicago, IL · On-site

ANALYTICS ENGINEER What the Job Entails: * Work with internal customers to understand their data ... Develop and maintain data pipelines to extract or ingest new data sources to a data warehouse ...

Traffic Tech Inc.

Analytics Engineer

Chicago, IL

ANALYTICS ENGINEER What the Job Entails: * Work with internal customers to understand their data ... Develop and maintain data pipelines to extract or ingest new data sources to a data warehouse ...

Loop

Analytics Engineer

Chicago, IL · On-site

$118K - $141K/yr

Loop is an AI-native company focused on transforming the logistics industry through innovative data solutions. As an Analytics Engineer, you will be responsible for designing and maintaining core ...

Loop

Analytics Engineer

Chicago, IL · On-site

$118K - $141K/yr

As an Analytics Engineer, you will design and maintain core data models and infrastructures, enabling data-driven decision-making for both internal teams and clients. Responsibilities : • Own Core ...

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All JobsData Analytics Engineer JobsData Analytics Engineer Jobs in Chicago, IL

Data Analytics Engineer information

See Chicago, IL salary details

$45.8K

$133.6K

$182.8K

How much do data analytics engineer jobs pay per year?

As of Jul 13, 2026, the average yearly pay for data analytics engineer in Chicago, IL is $133,597.00, according to ZipRecruiter salary data. Most workers in this role earn between $117,900.00 and $141,600.00 per year, depending on experience, location, and employer.

How do Data Analytics Engineers typically collaborate with data scientists and business stakeholders on projects?

Data Analytics Engineers play a crucial role in bridging the gap between raw data and actionable insights by building, optimizing, and maintaining data pipelines. They often work closely with data scientists to ensure data is clean, accessible, and structured for advanced analytics or machine learning models. Additionally, they collaborate with business stakeholders to understand reporting requirements and ensure that data solutions align with organizational objectives. Regular communication and cross-functional teamwork are essential aspects of this role, as engineers must translate business needs into technical specifications and deliver reliable data products.

Can a data engineer make 200k?

Data engineers can earn $200,000 or more annually, especially with experience, advanced skills in cloud platforms, big data tools, and certifications. Salaries vary by location, industry, and company size, with senior roles and those in high-demand markets more likely to reach or exceed this level.

What engineers make $500,000?

Senior data analytics engineers with extensive experience, advanced skills in data modeling, machine learning, and proficiency with tools like Python, SQL, and cloud platforms can reach salaries of $500,000 or more, especially in high-cost-of-living areas or within large tech companies. Achieving this level often requires a combination of technical expertise, leadership roles, and sometimes equity compensation.

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

To thrive as a Data Analytics Engineer, you need strong proficiency in data modeling, SQL, and statistical analysis, typically supported by a degree in computer science, statistics, or a related field. Familiarity with tools such as Python, R, Apache Spark, Tableau, and cloud data platforms like AWS or Google BigQuery is essential, along with relevant certifications. Excellent problem-solving, communication, and collaboration skills help you translate data insights into actionable business solutions. These skills and qualities are crucial for designing robust data pipelines and enabling data-driven decision-making across organizations.

Is 40 too late for data science?

Data Analytics Engineers and data science professionals can successfully transition into the field at age 40 or older, as skills such as programming, statistical analysis, and experience with tools like Python or SQL are valuable regardless of age. Many employers value diverse experience and lifelong learning, and certifications or online courses can help enhance credentials at any age.

What is the difference between Data Analytics Engineer vs Data Scientist?

AspectData Analytics EngineerData Scientist
CredentialsBachelor's or master's in CS, Data Science, or related fields; certifications like Google Data AnalyticsBachelor's or master's in CS, Statistics, or related fields; certifications like Certified Data Scientist
Work EnvironmentFocus on building data pipelines, dashboards, and analytics toolsFocus on statistical modeling, machine learning, and data exploration
Employer & Industry UsageUsed across tech, finance, healthcare for data infrastructure and analyticsCommon in research, product development, and advanced analytics teams

While both roles work with data, Data Analytics Engineers primarily develop data infrastructure and tools for analysis, whereas Data Scientists focus on statistical modeling and machine learning to generate insights. They often collaborate but have distinct technical focuses.

What does a data analytics engineer do?

A data analytics engineer designs, builds, and maintains data pipelines and systems to collect, process, and analyze large datasets. They use tools like SQL, Python, and cloud platforms to enable data-driven decision-making and often collaborate with data scientists and business teams to deliver actionable insights.
What are the most commonly searched types of Data Analytics Engineer jobs in Chicago, IL? The most popular types of Data Analytics Engineer jobs in Chicago, IL are:
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Data Analytics Engineer jobs near you
Infographic showing various Data Analytics Engineer job openings in Chicago, IL as of July 2026, with employment types broken down into 1% Internship, 91% Full Time, 6% Part Time, and 2% Contract. Highlights an 79% Physical, 5% Hybrid, and 16% Remote job distribution, with an average salary of $133,597 per year, or $64.2 per hour.

Data Analytics Engineer - Chicago

Steame LLC

Chicago, IL • On-site

$120K - $130K/yr

Full-time

Re-posted 15 days ago

Job description

Who We Are
STEAMe is a workforce technology company turning fragmented systems into engines of economic advancement. Our roots in NowPow-a nationally recognized social care referral platform that connected 13 million people to vital care services-taught us how to deliver multi-sided platforms that power complex ecosystems. We channel that expertise into STEAMe, with purpose-built workforce solutions that close data and process gaps, connect stakeholders, and accelerate job placement and prosperity at scale.The Role
As a Data Analytics Engineer at STEAMe, you will sit at the intersection of analytics, data engineering, and emerging AI-powered workflows. You'll be responsible for building reliable data pipelines, transforming data for analysis, and delivering high-quality dashboards and reports that drive product, operational, and customer insights.
Working closely with product, engineering, customer success, and business stakeholders, you'll own data transformations, support analytics architecture, and help evolve how STEAMe uses data - including experimenting with LLM-assisted analysis and prompt-based workflows to surface insights more efficiently.
This is an excellent opportunity for someone who enjoys working across the full data lifecycle - from ingestion and modeling to visualization and insight delivery, - in a fast-paced startup environment.Key Responsibilities
  • Partner with cross-functional teams to understand business objectives and translate them into scalable data models, metrics, and analytics solutions
  • Design, build, and maintain data transformations and lightweight ETL pipelines using SQL and Python
  • Develop and maintain curated analytics tables and semantic layers to support reporting and dashboards
  • Create and manage dashboards and reports in BI tools (e.g., Tableau, Looker, Power BI) for internal teams and external partners
  • Ensure data accuracy, consistency, and reliability across analytics outputs
  • Support and evolve data architecture by collaborating with engineering on source systems, data flows, and integrations
  • Write Python scripts for data preparation, automation, and analytics workflows
  • Experiment with and develop LLM-enabled workflows, including prompt design, to extract insights, summarize data, or support internal analytics use cases
  • Experiment with AI tools to deliver new methodologies and optimize workflows
  • Document data models, pipelines, metrics definitions, and analytics best practices
  • Troubleshoot data quality issues and proactively identify opportunities to improve data processes and performance
Requirements
  • Bachelor's degree in Analytics, Computer Science, Engineering, Statistics, Economics, Mathematics, or a related field (or equivalent experience)
  • 3-6 years of experience in analytics, analytics engineering, or a data engineering-adjacent role
  • Strong proficiency in SQL and Python
  • Experience building and maintaining data pipelines, transformations, or ETL processes
  • Hands-on experience with BI and visualization tools (e.g., Tableau, Looker, Power BI)
  • Solid understanding of data modeling concepts and analytics best practices
  • Ability to communicate clearly with both technical and non-technical stakeholders
  • Comfortable working in a fast-moving startup environment with evolving requirements

Preferred Qualifications
  • Experience with cloud data platforms (e.g., AWS, GCP, or Azure)
  • Familiarity with modern analytics stacks (e.g., dbt or similar transformation tools)
  • Experience working with SaaS platforms or in edtech / workforce development environments
  • Exposure to data orchestration tools and APIs
  • Experience using or designing LLM-powered analytics workflows or prompt-based tools

Environmental Job Requirements & Working Conditions
  • This position is based in Chicago, IL
  • STEAMe is a Hybrid work environment, with 3 days work from home and 2 days in-office work
  • The pay range for this role is: $120,000 - 130,000. This salary range represents our target hiring range. Final compensation will be determined based on a variety of factors, including experience, skill set, and alignment to the role's scope and level.
Please note: This position is not eligible for current or future employment sponsorship.
STEAMe is committed to building a diverse team and fostering an inclusive culture, and is proud to be an equal opportunity employer. We embrace and encourage our employees' differences in race, religion, color, national origin, gender, family status, sexual orientation, gender identity, gender expression, age, veteran status, disability, pregnancy, medical conditions, and other characteristics.

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