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Data Engineer Sports Analytics Jobs in Bridgeview, IL

Magid Glove & Safety

Data Engineer

Romeoville, IL · On-site

$116K - $140K/yr

Job Summary The Data Engineer plays a crucial, cross-functional role here at Magid. This is a high ... Well-documented datasets and advanced semantic models that enable reporting and analysis * Data ...

IMC

Data Engineer

Chicago, IL · On-site

$175K - $225K/yr

We are seeking a dedicated and experienced Data Engineer to join our Chicago team. The ideal ... Strong statistical analysis skills * Demonstrated ability to troubleshoot and conduct root-cause ...

hightower

Data Engineer

Chicago, IL · Hybrid

$100K - $115K/yr

You will work closely with data scientists, analysts, and engineers across the firm to deliver reliable, well-modeled data into Snowflake and our operational data stores. What You'll Do * Build and ...

Prolaio

Data Engineer

Chicago, IL · On-site

$134K/yr

... power advanced analytics and machine learning models. You'll work closely with data scientists ... This role will report to the Lead Data Engineer. We would love to find someone in the Chicagoland ...

IMC B.V.

Data Engineer

Chicago, IL · On-site

$175 - $225/hr

We are seeking a dedicated and experienced Data Engineer to join our Chicago team. The ideal ... Strong statistical analysis skills * Demonstrated ability to troubleshoot and conduct root‑cause ...

Co-Sourcing Partners

GCP Data Engineer

Chicago, IL · On-site

$118K - $141K/yr

GCP Data Engineer Duration: 6 months Contract to hire Location: Chicago is the preferred location ... Write advanced SQL queries for transformation, validation, and analytics. * Develop scalable data ...

Benchmark Analytics

Senior Data Engineer

Chicago, IL · On-site

$109K - $148K/yr

Benchmark Analytics provides a comprehensive, all-in-one solution that is advancing police force ... This is a senior individual contributor role for a deeply experienced Data Engineer who can ...

Cesco

Data Engineer

Elk Grove Village, IL · On-site

$113K - $135K/yr

You will partner closely with the BI & Analytics Developer(s) and business stakeholders to ensure the underlying data is accurate, well-governed, and structured to support self-service reporting and ...

Benchmark Analytics

Senior Data Engineer

Chicago, IL · On-site

$109K - $148K/yr

Benchmark Analytics provides a comprehensive, all-in-one solution that is advancing police force ... This is a senior individual contributor role for a deeply experienced Data Engineer who can ...

McDonald's

Data Engineer III

Chicago, IL · On-site

$117K - $141K/yr

The Enterprise Data, Analytics, and AI (EDAA) organization empowers every function - Marketing ... McDonald's is hiring a Data Engineer III focused on Data Clean Room data ingestion, curation, and ...

1872 Consulting

Azure Data Engineer

Chicago, IL · Hybrid

$118K - $141K/yr

zure Data Engineer NYC, NY (Midtown) - hybrid WFH Summary s a crucial member of our Data and AI team, this role is pivotal in driving our data strategy and achieving our analytical goals. The ...

1 point system

Data Engineer

Chicago, IL · On-site

$118K - $141K/yr

... analytics, and downstream consumption Data Platform & IntegrationIntegrate the Data Lakehouse with enterprise tools such as Tableau, Alteryx, and machine learning platforms Design and implement data ...

1872 Consulting

Azure Data Engineer

Chicago, IL · Hybrid

$118K - $141K/yr

zure Data Engineer NYC, NY (Midtown) - hybrid WFH Summary s a crucial member of our Data and AI team, this role is pivotal in driving our data strategy and achieving our analytical goals. The ...

Rush University Medical Center

Data Engineer

Chicago, IL · On-site

$46.07 - $68.64/hr

The Data Engineer is responsible for designing and implementing data pipelines for cloud projects ... for analysts. Exemplifies the Rush mission, vision and values and acts in accordance with Rush ...

Tiger Analytics

Senior Data Engineer

Chicago, IL · On-site

$130 - $180/hr

Tiger Analytics is a fast-growing advanced analytics consulting firm. Our consultants bring deep ... We are seeking an experienced Data Engineer to join our data team. In this role, you will be ...

Collegis LLC

Data Engineer

Oak Brook, IL · On-site

$80K - $110K/yr

Bachelor's or Master's Degree in MIS, IS, Business Analytics, Computer Science, a related field, or equivalent experience. * 2-5 years of experience in data engineering. * Advanced SQL, plus bash and ...

SYSTEGRATION INC

dbt / Data Engineer

Des Plaines, IL · On-site

$111K - $134K/yr

dbt / Data Engineer Direct Client Location: Des Plaines, IL -- Hybrid, ~50% onsite Engagement ... and analytics platform. · Design, develop, test, and deploy production-grade dbt models ...

Collegis Education

Data Engineer

Oak Brook, IL · On-site

$115K - $138K/yr

Bachelor's or Master's Degree in MIS, IS, Business Analytics, Computer Science, a related field, or equivalent experience. * 2-5 years of experience in data engineering. * Advanced SQL, plus bash and ...

SYSTEGRATION INC

dbt / Data Engineer

Des Plaines, IL · On-site

$111K - $134K/yr

dbt / Data Engineer Direct Client Location: Des Plaines, IL -- Hybrid, ~50% onsite Engagement ... and analytics platform. · Design, develop, test, and deploy production-grade dbt models ...

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Showing results 41-60

All JobsData Engineer Sports Analytics JobsData Engineer Sports Analytics Jobs in Bridgeview, IL

Data Engineer Sports Analytics information

See Bridgeview, IL salary details

$45.4K

$132.5K

$181.3K

How much do data engineer sports analytics jobs pay per year?

As of Sep 6, 2026, the average yearly pay for data engineer sports analytics in Bridgeview, IL is $132,466.00, according to ZipRecruiter salary data. Most workers in this role earn between $116,900.00 and $140,400.00 per year, depending on experience, location, and employer.

What does a data engineer in sports analytics do?

A Data Engineer in Sports Analytics designs, builds, and maintains the infrastructure and systems that collect, store, and process large volumes of sports-related data. They ensure data pipelines are efficient and reliable so that analysts and data scientists can access accurate information for player performance analysis, game strategy, and business decisions. Their work involves integrating data from various sources, optimizing databases, and implementing best practices in data security and quality, all within the context of the sports industry.

What are the key skills and qualifications needed to thrive as a data engineer in sports analytics?

To thrive as a Data Engineer in Sports Analytics, you need a strong background in computer science, data modeling, and database management, typically supported by a relevant degree and experience with large data sets. Familiarity with tools and technologies such as SQL, Python, Spark, cloud platforms (AWS, Azure), and ETL pipelines is essential, and certifications in these areas can be advantageous. Excellent problem-solving, teamwork, and communication skills help you collaborate with analysts, coaches, and stakeholders to translate data into actionable insights. These competencies ensure the efficient collection, processing, and delivery of high-quality sports data that drive performance analysis and competitive advantage.

How does a data engineer in sports analytics typically collaborate with data scientists and analysts on a project?

As a Data Engineer in Sports Analytics, you’ll regularly work alongside data scientists and analysts to ensure high-quality, reliable data is available for modeling and analysis. Your responsibilities often include building and maintaining data pipelines, transforming raw sports data into usable formats, and optimizing data storage for performance. Effective communication is key, as you’ll need to understand the analytical requirements and adjust pipelines or data sources accordingly. Collaboration often happens through regular meetings, shared documentation, and close feedback loops to align on project goals and data needs.

What is the difference between Data Engineer Sports Analytics vs Data Analyst Sports Analytics?

AspectData Engineer Sports AnalyticsData Analyst Sports Analytics
Primary FocusBuilding and maintaining data pipelines, infrastructure, and databasesAnalyzing data, generating reports, and providing insights
Skills & CertificationsSQL, Python, data warehousing, cloud platformsExcel, SQL, statistical analysis, visualization tools
Work EnvironmentData engineering teams, IT infrastructureBusiness teams, sports analytics departments
Industry UsageSports organizations, tech companies supporting sports dataSports teams, media outlets, betting companies

While Data Engineer Sports Analytics focuses on building and maintaining the data infrastructure necessary for sports data analysis, Data Analyst Sports Analytics concentrates on interpreting that data to generate actionable insights. Both roles are essential in sports analytics but serve different functions within the data ecosystem.

What job categories do people searching Data Engineer Sports Analytics jobs in Bridgeview, IL look for?

The top searched job categories for Data Engineer Sports Analytics jobs in Bridgeview, IL are:

What cities near Bridgeview, IL are hiring for Data Engineer Sports Analytics jobs?

Cities near Bridgeview, IL with the most Data Engineer Sports Analytics job openings:

Data Engineer Sports Analytics jobs near you

Data Engineer

Magid Glove & Safety

Romeoville, IL • On-site

$116K - $140K/yr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 29 days ago

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

Hybrid Work Schedule:Monday - Thursday onsite at our corporate office in Romeoville, IL; Fridays WFH.
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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