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Data Modeling Internship Jobs in Illinois (NOW HIRING)

Magid Glove & Safety

Data Engineer

Romeoville, IL · On-site

$116K - $140K/yr

Well-documented datasets and advanced semantic models that enable reporting and analysis * Data ... internships or equivalent projects) * Ability to write production-quality SQL and create reliable ...

New

Imperial PFS

Analytics Engineer

Edwardsville, IL · On-site

$107K - $129K/yr

Building standardized data models that reduce time-to-insight for business users * Implementing ... Interns joining our team gain hands-on exposure to a dynamic industry, working alongside ...

Walker Consultants

Data Platform Engineer

Chicago, IL · Hybrid

$85K - $120K/yr

... internships/co-ops count). * Experience developing or supporting Power BI reports and dashboards, including Power Query, data modeling, DAX measures, and scheduled refreshes. * Strong SQL skills ...

MessageControl

Data Scientist

Chicago, IL · On-site

Must have at least 3 years of professional experience outside of academic or internship settings. Prior research, data science modeling and taking machine learning features to market. * Outstanding ...

MessageControl

Data Scientist

Chicago, IL · On-site

Must have at least 3 years of professional experience outside of academic or internship settings. Prior research, data science modeling and taking machine learning features to market. * Outstanding ...

State Farm

Data Scientist

Bloomington, IL · On-site

Develops models that support State Farm's insurance pricing and underwriting decisions Data Science ... Lead/mentor other Data Scientists, interns, and other technical work teams * Make strategic ...

State Farm

Data Scientist

Bloomington, IL · Hybrid

Develops models that support State Farm's insurance pricing and underwriting decisions Data Science ... Lead/mentor other Data Scientists, interns, and other technical work teams * Make strategic ...

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Data Modeling Internship information

What is a data modeling internship?

A Data Modeling Internship is a temporary position for students or recent graduates to gain practical experience in designing and structuring data for use in databases and information systems. Interns typically work with data architects and analysts to create data models, which help organize and manage data efficiently for businesses. This role often involves learning about different data modeling techniques, using specialized software tools, and supporting projects that improve data quality and accessibility. The internship provides valuable exposure to real-world data challenges and prepares individuals for future roles in data management and analytics.

What is the difference between Data Modeling Internship vs Data Analyst Internship?

AspectData Modeling InternshipData Analyst Internship
Required SkillsData modeling, database design, SQL, data warehousingData analysis, Excel, SQL, visualization tools
Work EnvironmentData teams, IT departments, database environmentsBusiness units, analytics teams, reporting environments
Industry UsageTech, finance, healthcare, where data structure design is keyMarketing, finance, retail, focusing on data insights

While both internships involve working with data, a Data Modeling Internship focuses on designing and structuring data systems, whereas a Data Analyst Internship emphasizes analyzing data to generate insights. The choice depends on whether you prefer working on database architecture or data interpretation.

What are the key skills and qualifications needed to thrive as a data modeling intern, and why are they important?

To thrive as a Data Modeling Intern, you need a solid understanding of database concepts, data structures, and proficiency in SQL, often supported by coursework in computer science or data analytics. Familiarity with data modeling tools like ERwin, Microsoft Visio, or Lucidchart, and experience with relational database management systems (RDBMS) are typically required. Strong analytical thinking, attention to detail, and effective communication skills help interns collaborate with teams and translate business requirements into data models. These skills are essential for creating accurate, scalable data models that support efficient data storage, retrieval, and analysis in organizational projects.

What types of projects and responsibilities can I expect during a data modeling internship?

As a Data Modeling Intern, you can expect to work closely with data engineers and analysts to design, build, and refine data models that support business intelligence and analytics initiatives. Typical responsibilities include gathering requirements, creating entity-relationship diagrams, normalizing databases, and assisting in the documentation of data flows. You'll also have opportunities to participate in meetings with cross-functional teams, learn best practices for database design, and contribute to ongoing data quality improvement efforts. This hands-on experience provides valuable exposure to real-world data challenges and helps build a strong foundation for a career in data management.
What are the most commonly searched types of Data Modeling jobs in Illinois? The most popular types of Data Modeling jobs in Illinois are:
What cities in Illinois are hiring for Data Modeling Internship jobs? Cities in Illinois with the most Data Modeling Internship job openings:
Data Modeling Internship jobs near you

Data Engineer

Magid Glove & Safety

Romeoville, IL • On-site

$116K - $140K/yr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted yesterday

New

Job description

Description
What Matters at Magid? YOU do!
"The number one key to growth is having good people and that's what has driven us at every stage of the game." - Greg Cohen, CEO
At Magid, we're not just passionate about safety-we're passionate about people. As an industry leader, we've built an innovative and collaborative environment where diversity is celebrated, ideas are valued, and personal and professional growth never stops.
Job Summary
The Data Engineer plays a crucial, cross-functional role here at Magid. This is a high-visibility role where your efforts will have impact on all levels of the organization. Our work spans product sourcing, customer journeys, service delivery, sales workflows, and the platforms and SME's that support them. We have seen a drastic increase in adoption of the Data Engineer's services. We are embedding data culture into our DNA and are excited to add a new face to that mission.
Essential Responsibilities
  • Data pipelines and transformations (ingest, clean, vet, test, transform, publish)
  • Well-documented datasets and advanced semantic models that enable reporting and analysis
  • Data quality checks (freshness, completeness, validity) and participation in monitoring/alerting
  • Datasets that support machine learning use cases with clear definitions
  • Incremental improvements to pipeline performance, cost, and reliability with guidance
  • Collaboration with partners to clarify requirements and iterate on data products
  • Partner in Data Discovery & Solution Shaping
  • Develop Power BI Solutions that are iterative while supporting our current ecosystem of analytics driven reporting
  • Learn source systems and data flows; help map entities, identifiers, and key business rules
  • Contribute to data modeling and design decisions with guidance (schemas, grain, slowly changing dimensions, etc.)
  • Propose simpler, more reliable approaches (e.g., reuse shared datasets, standardize definitions) to improve trust and increase adoption

Build & Maintain Data Pipelines
  • Build and maintain batch and/or streaming pipelines to ingest data from source systems into our analytical platform
  • Develop transformations to clean, standardize, and enrich data using agreed-upon patterns and tools (e.g., SQL, Python, Fabric Data Lake, KQL)
  • Support ML workflows by helping produce curated training datasets and feature-ready tables, following established patterns
  • Help monitor pipeline health and data quality; investigate variances and propose code enhancements to key datasets.

Contribute to a Strong Data Culture
  • Help evolve data standards (naming conventions, modeling patterns, documentation) to improve consistency and reuse
  • Promote a culture of data trust through quality checks, clear definitions, and thoughtful change management
  • Willingness to tackle obscure requests and find ways to solve cumbersome outdated workflows

How We Work
  • Empowered to solve problems, not just build features
  • Accountable for outcomes, not output
  • Collaborative by default, from discovery through delivery
  • Continuously learning, using data, AI/ML and customer insight to improve

Magid offers a variety of benefits to our team members including:
  • Health, dental, vision, life and disability insurance
  • Bonus plan
  • 401k retirement plan with company match
  • Company provided Profit Sharing
  • Participation in Magid Paid Time Off (PTO) Policy
  • 9 Paid Holidays

Requirements
  • Bachelor's degree in Computer Science, Engineering, or a related field
  • Equivalent practical experience is equally valued
  • Strong SQL fundamentals (joins, aggregation, window functions, performance basics)
  • Data modeling mindset: Cares about clear definitions, grain, and making data usable
  • Pragmatic problem solving: Debugs issues, makes sensible tradeoffs, and knows when to ask for help
  • Ownership: Takes responsibility for assigned datasets/pipelines and follows through to production
  • Collaboration: Works effectively with product managers to deliver trusted data

Key Qualifications
  • Minimum of 5+ years of experience in data engineering, analytics engineering, or software engineering (including internships or equivalent projects)
  • Ability to write production-quality SQL and create reliable transformations with attention to correctness
  • Understanding of dimensional modeling and/or event modeling concepts (fact/dimension tables, star schemas)
  • Proficiency in Python (or similar) and comfort using Git and code reviews to collaborate
  • Familiarity with data platforms (data warehouse/lakehouse concepts), and exposure to orchestration/ETL tools (e.g., Airflow, dbt, Spark) is a plus

Preferred Qualifications
  • Experience working with a modern data warehouse/lakehouse (e.g., Microsoft Fabric One Lake, Snowflake, BigQuery, Databricks)
  • Exposure to data quality testing, monitoring, or observability concepts
  • Familiarity with data governance concepts (Row-Level-Security, Workspace Roles, etc)
  • Exposure to machine learning workflows (training data preparation, feature tables, model experimentation support)
  • Familiarity with modern engineering practices (CI/CD, testing, observability)

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