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Data Engineering Jobs in Elgin, IL (NOW HIRING)

Randstad Digital

Data Engineering Manager

Chicago, IL · On-site

$165K - $185K/yr

Role OverviewThe Data Engineering Manager will lead a team of approximately 7-9 data engineers/consultants supporting the continued delivery of Sidley's enterprise Databricks data platform.The ...

Sidley Austin LLP

Data Engineering Manager

Chicago, IL · On-site

The Data Engineering Manager will lead a scrum team of data engineers in the design, development, and delivery of Sidley's enterprise Databricks data platform. This role blends hands-on technical ...

The Aspen Group

Manager, Data Engineering

Chicago, IL · On-site

$160K - $190K/yr

The Manager, Data Engineering leads the design, delivery, and reliability of TAG's enterprise data platform across our multi-brand environment. It's a hands-on leadership role covering people ...

Aspen Group, Inc.

Manager, Data Engineering

Chicago, IL · On-site

$160K - $190K/yr

The Manager, Data Engineering leads the design, delivery, and reliability of TAG's enterprise data platform across our multi-brand environment. It's a hands-on leadership role covering people ...

The Aspen Group

Manager, Data Engineering

Chicago, IL · On-site

$160K - $190K/yr

The Manager, Data Engineering leads the design, delivery, and reliability of TAG's enterprise data platform across our multi-brand environment. It's a hands-on leadership role covering people ...

Gallagher

Data Engineering Manager

Rolling Meadows, IL · Hybrid

Overview The Data Engineering Manager will be responsible for the design, development, implementation, and support of the Data Initiatives throughout Gallagher, ensuring that optimal data delivery ...

JLL

Sr. Director, Data Engineering

Chicago, IL · On-site

The ideal candidate blends Principal Data Engineer-level technical credibility - expert data engineering, cloud architecture, and cross-domain platform delivery - with proven experience managing ...

AirLife

Data Engineering & Platform Manager

Deerfield, IL · Remote

$117K - $140K/yr

POSITION SUMMARY The Data Engineering & Platform Manager is AirLife's technical owner of the enterprise data platform -- responsible for building, governing, and continuously improving the data ...

Clarus

Sr Manager, Data Engineering

Chicago, IL · On-site +1

Role Overview We are seeking an experienced and hands-on Senior Manager, Data Engineering to lead the strategy, architecture, and execution of Clarus' modern data platform. This role will be ...

Geneva Trading

Data Engineering Manager

Chicago, IL · On-site

The Role We are looking for a Data Engineering Manager to own our market data platforms and analytical data systems. This is not a pure people-management role. You will manage a small team, but you ...

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All JobsData Engineering JobsData Engineering Jobs in Elgin, IL

Data Engineering information

See Elgin, IL salary details

$45.5K

$163.1K

$240.7K

How much do data engineering jobs pay per year?

As of Sep 1, 2026, the average yearly pay for data engineering in Elgin, IL is $163,122.00, according to ZipRecruiter salary data. Most workers in this role earn between $132,000.00 and $168,000.00 per year, depending on experience, location, and employer.

What is data engineering?

A Data Engineering job involves designing, building, and maintaining the infrastructure that enables efficient data collection, storage, and processing. Data Engineers develop pipelines to transform raw data into usable formats for analytics and machine learning. They work with databases, big data technologies, and cloud platforms to ensure data is accessible and reliable. Their role is crucial for organizations to make data-driven decisions and optimize business processes.

What does a data engineer do?

Data Engineers regularly design, build, and maintain scalable data pipelines to support analytics and business intelligence teams. Their daily tasks often involve working with large datasets, optimizing data storage, ensuring data integrity, and troubleshooting data-related issues. Collaboration with data scientists, analysts, and software engineers is common to align on data requirements and improve workflows. You may also participate in regular code reviews and contribute to the ongoing improvement of data infrastructure. This role is ideal for problem-solvers who enjoy working with both code and complex systems in a collaborative, fast-paced environment.

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

To thrive in Data Engineering, you need a solid background in programming (such as Python, Java, or Scala), data modeling, and database management, typically supported by a degree in computer science or a related field. Familiarity with ETL tools, cloud platforms like AWS or Azure, big data frameworks (e.g., Hadoop, Spark), and relevant certifications is highly valued. Strong problem-solving abilities, effective communication, and the ability to work collaboratively across teams are key soft skills for this role. These attributes are crucial for designing robust data pipelines, ensuring data quality, and enabling organizations to make data-driven decisions efficiently.

Are data engineers still in demand?

Data engineers are currently in high demand due to the increasing reliance on data-driven decision making and the growth of big data technologies. They typically need skills in SQL, cloud platforms, and tools like Apache Spark or Hadoop, and job opportunities are expected to remain strong as organizations continue to prioritize data infrastructure.

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

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

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

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

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

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

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

Data Engineering jobs near you
Infographic showing various Data Engineering job openings in Elgin, IL as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 13% Part Time, and 3% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution, with an average salary of $163,122 per year, or $78.4 per hour.

Data Engineering Manager

Randstad Digital

Chicago, IL • On-site

$165K - $185K/yr

Other

Posted 7 days ago

Job description

job summary:

Role OverviewThe Data Engineering Manager will lead a team of approximately 7-9 data engineers/consultants supporting the continued delivery of Sidley's enterprise Databricks data platform.The platform architecture and core infrastructure are largely established. This role is therefore less about defining architecture from scratch and more about technical execution, data transformation, team leadership, and delivery. The manager will work closely with Data Architecture and BI to ensure data is appropriately ingested, transformed, and prepared for downstream reporting and dashboards.What We Are Looking ForPlease prioritize candidates with: - Strong data engineering fundamentals: 5+ years of hands-on data engineering experience with pipelines, ETL/ELT, data transformation, and modern cloud data platforms. - Recent technical depth: This person will not be expected to write production code regularly, but must still be close enough to the technology to read and review code, assess quality, understand architecture, troubleshoot issues, and provide credible technical direction. - People leadership: Ideally 2-4 years of recent mentorship/management experience. Strong Lead-level candidates with meaningful people-management experience may also be considered. - Leadership presence: We need someone assertive and confident enough to drive execution, hold engineers and consultants accountable, resolve conflict, manage performance, and keep the team moving. Communication skills and leadership presence will be important throughout the interview process.Think of the role as approximately 60% technical / 40% leadership, while recognizing this is ultimately a people-management position.TechnologyAzure Databricks specifically is NOT required. Please do not screen out strong candidates simply because their experience is on another cloud or comparable data platform. Strong experience with Databricks, Snowflake, or similar modern data platforms is relevant. Candidates should understand modern data architecture and be comfortable with technologies/concepts such as Python, SQL, ETL/ELT, Lakehouse architecture, CI/CD, testing, and data quality. Azure experience is preferred, but strong AWS/Google Cloud Platform cloud candidates should absolutely be considered.


location: Chicago, Illinois
job type: Permanent
salary: $165,000 - 185,000 per year
work hours: 9am to 4pm
education: Bachelors
responsibilities:

The Data Engineering Manager will lead a scrum team of data engineers in the design, development, and delivery of Sidley's enterprise Databricks data platform. This role blends hands-on technical leadership with people management, balancing day-to-day engineering execution with longer-term architectural direction. Partnering closely with the Data Architect, analytics, and business teams, the Data Engineering Manager will set technical standards, drive data quality, and ensure the team delivers scalable, reliable, and governed data solutions. This role reports to the Senior Manager of Data Platform & Engineering.


Duties and Responsibilities:



  • Manage, mentor, and develop a scrum team of 5-7 data engineers, fostering a culture of technical excellence, collaboration, and continuous improvement.

  • Conduct regular one-on-ones, performance reviews, and career development conversations to support individual growth and team retention.

  • Resolve team impediments and shield engineers from organizational friction so they can focus on delivery.

  • Set and enforce technical direction for the team, including coding standards, design patterns, and engineering best practices across the Databricks data platform.

  • Lead and participate in technical design sessions, translating complex business and data requirements into scalable, well-architected solutions.

  • Drive the design and evolution of the Lakehouse architecture (Bronze/Silver/Gold) on Azure Databricks, including Delta Lake, Apache Spark, and ADLS Gen2.

  • Collaborate with the Data Architect to align platform implementation with enterprise data models, domain definitions, and governance standards.

  • Own and facilitate the code review process, ensuring all production code meets quality, performance, and maintainability standards.

  • Establish and enforce data quality frameworks, including validation, monitoring, alerting, and SLA adherence across pipelines and data products.

  • Oversee the end-to-end design, development, and operation of scalable ETL and streaming data pipelines on Azure Databricks, leveraging PySpark, Spark SQL, Delta Lake, and Databricks Workflows.

  • Drive the development of reusable, metadata-driven ingestion frameworks and modular data transformation patterns.

  • Troubleshoot and resolve complex platform, infrastructure, and pipeline issues, ensuring minimal downtime and optimal performance.


Education and/or Experience:

Required:



  • Bachelor's degree in Computer Science, Engineering, Data Science, or a related field.

  • A minimum of 5 years of hands-on experience in data engineering, including designing and building scalable data pipelines and ETL/ELT processes.

  • A minimum of 2 years of experience managing or leading a team of data engineers, including direct people management responsibilities.

  • Strong expertise in Azure Databricks, Delta Lake, Databricks SQL, Apache Spark, Unity Catalog, Databricks Workflows, or similar data platforms.

  • Proficiency with Python and SQL for large-scale data processing.

  • Proven experience with Lakehouse architecture patterns (Bronze/Silver/Gold), schema evolution, and data modeling for analytics and operational workloads.

  • Demonstrated experience driving code reviews, setting engineering standards, and instilling data quality and testing disciplines within a team.

  • Experience with CI/CD pipelines, version control, automated testing, and monitoring in a data engineering context.

  • Hands-on experience with cloud data platforms in Azure, AWS, or Google Cloud Platform, with Azure strongly preferred.

  • Strong communication and stakeholder management skills, with the ability to translate between technical and business contexts.


Preferred:

  • Master's degree in Computer Science, Engineering, or a related field.

  • Experience integrating Azure Databricks with Azure DevOps, ADLS Gen2, and Azure Key Vault.

  • Familiarity with enterprise data modeling, data governance frameworks, and metadata management tools such as Unity Catalog or Collibra.

  • Experience with Infrastructure as Code (IaC) and Governance as Code practices.

  • Familiarity with machine learning workloads and feature engineering in a Lakehouse environment.

  • Experience leading data engineering teams in an agile or scrum delivery model.

  • Industry experience in legal or professional services a plus.


Other Skills and Abilities:

The following will also be required of the successful candidate:



  • Strong organizational and project management skills.

  • Strong attention to detail and commitment to quality.

  • Good judgment and sound decision-making under pressure.

  • Strong interpersonal and communication skills.

  • Able to work harmoniously and effectively with others across technical and business teams.

  • Able to preserve confidentiality and exercise discretion.

  • Able to manage multiple priorities and competing deadlines


qualifications:

Education and/or Experience:


Required:


Bachelor's degree in Computer Science, Engineering, Data Science, or a related field.


A minimum of 5 years of hands-on experience in data engineering, including designing and building scalable data pipelines and ETL/ELT processes.


A minimum of 2 years of experience managing or leading a team of data engineers, including direct people management responsibilities.


Strong expertise in Azure Databricks, Delta Lake, Databricks SQL, Apache Spark, Unity Catalog, Databricks Workflows, or similar data platforms.


Proficiency with Python and SQL for large-scale data processing.


Proven experience with Lakehouse architecture patterns (Bronze/Silver/Gold), schema evolution, and data modeling for analytics and operational workloads.


Demonstrated experience driving code reviews, setting engineering standards, and instilling data quality and testing disciplines within a team.


Experience with CI/CD pipelines, version control, automated testing, and monitoring in a data engineering context.


Hands-on experience with cloud data platforms in Azure, AWS, or Google Cloud Platform, with Azure strongly preferred.


Strong communication and stakeholder management skills, with the ability to translate between technical and business contexts.


Preferred:


Master's degree in Computer Science, Engineering, or a related field.


Experience integrating Azure Databricks with Azure DevOps, ADLS Gen2, and Azure Key Vault.


Familiarity with enterprise data modeling, data governance frameworks, and metadata management tools such as Unity Catalog or Collibra.


Experience with Infrastructure as Code (IaC) and Governance as Code


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