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Data Engineer Sports Analytics Jobs (NOW HIRING)

Tredence Analytic

Data Engineer

Chicago, IL

$118K - $141K/yr

Company Description Tredence is a global analytics services and solutions company. Our capabilities range from Data Engineering, Visualization, Data Management to Advanced analytics, Big Data, Cloud ...

Tredence Analytic

Data Engineer

Chicago, IL · On-site

$118K - $141K/yr

Company Description Tredence is a global analytics services and solutions company. Our capabilities range from Data Engineering, Visualization, Data Management to Advanced analytics, Big Data, Cloud ...

Index Analytics

Data Engineer

Baltimore, MD · On-site +1

$126K - $142K/yr

Index Analytics, LLC, is a rapidly growing Baltimore-based small business providing health related ... Job Overview As a Data Engineer in this role, you will apply advanced data engineering principles ...

Data Ideology

Data Engineer

Pittsburgh, PA · Remote

$117K - $140K/yr

Our data analytics advisory services enable our customers to transform data into insights by ... Data Engineer will leverage their business and technical knowledge to develop production-ready data ...

Data Ideology

Data Engineer

Pittsburgh, PA · On-site +1

$111K - $133K/yr

Our data analytics advisory services enable our customers to transform data into insights by ... Data Engineer will leverage their business and technical knowledge to develop production-ready data ...

NEP GROUP

Data Engineer

Dallas, TX · On-site +1

$113K - $136K/yr

Partner with BI and ML teams to support analytics and advanced data use cases * Identify ... Weve supported some of the worlds most watched productions and live events in sports, entertainment ...

US Mobile

Analytics Data Engineer

New York, NY

$125K - $150K/yr

We're looking for an Analytics Data Engineer to help build, scale, and maintain the data foundation that powers decision-making across the company. You'll work closely with stakeholders across ...

US Mobile

Analytics Data Engineer

New York, NY · On-site

$140K - $190K/yr

We're looking for an Analytics Data Engineer to help build, scale, and maintain the data foundation that powers decision-making across the company. You'll work closely with stakeholders across ...

INDEX ANALYTICS LLC

Data Engineer

Baltimore, MD · Remote

$116K - $139K/yr

Index Analytics, LLC, is a rapidly growing Baltimore-based small business providing health related ... Job Overview As a Data Engineer in this role, you will apply advanced data engineering principles ...

OC Sports and Entertainment

Lead Data Engineer

Anaheim, CA · On-site

$140K - $180K/yr

Join our team to help create and develop the future of live entertainment and sports in Orange ... analytics, operations, and decision-making. Responsibilities * Design and build a governed data ...

US Mobile

Analytics Data Engineer

New York, NY · On-site

$140K - $190K/yr

We're looking for an Analytics Data Engineer to help build, scale, and maintain the data foundation that powers decision-making across the company. You'll work closely with stakeholders across ...

NEP Group

Data Engineer

Pittsburgh, PA · On-site

$111K - $133K/yr

Partner with BI and ML teams to support analytics and advanced data use cases * Identify ... We've supported some of the world's most watched productions and live events in sports ...

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All JobsData Engineer Sports Analytics Jobs

Data Engineer Sports Analytics information

See salary details

$44.5K

$129.7K

$177.5K

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

As of Jun 29, 2026, the average yearly pay for data engineer sports analytics in the United States is $129,716.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,500.00 and $137,500.00 per year, depending on experience, location, and employer.

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 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, and why are they important?

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.
More about Data Engineer Sports Analytics jobs
What cities are hiring for Data Engineer Sports Analytics jobs? Cities with the most Data Engineer Sports Analytics job openings:
What states have the most Data Engineer Sports Analytics jobs? States with the most job openings for Data Engineer Sports Analytics jobs include:
What job categories do people searching Data Engineer Sports Analytics jobs look for? The top searched job categories for Data Engineer Sports Analytics jobs are:
Data Engineer Sports Analytics jobs near you
Infographic showing various Data Engineer Sports Analytics job openings in the United States as of June 2026, with employment types broken down into 97% Full Time, and 3% Part Time. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $129,716 per year, or $62.4 per hour.

Data Engineer

Tredence Analytic

Chicago, IL

$118K - $141K/yr

Full-time

Posted 8 days ago

Job description

Company Description

Tredence is a global analytics services and solutions company. Our capabilities range from Data Engineering, Visualization, Data Management to Advanced analytics, Big Data, Cloud and Machine Learning. Our uniqueness is in bringing the right mix of technology and business analytics to create sustainable white-box solutions that are transitioned to our clients at the end of the engagement. We do this cost effectively using a global execution model leveraging our clients' existing technology and data assets. We also come in with strong IP and pre-built analytics solutions in data mining, business intelligence and Big Data.

Job Description

We are searching for an accountable, multitalented Data Engineer to facilitate the operations of our Data Scientists. The ideal candidate will be responsible for employing machine learning techniques to create and sustain structures that allow for the analysis of data, while remaining familiar with dominant programming and deployment strategies in the field. During various aspects of this process, you should collaborate with coworkers to ensure that your approach meets the needs of each project.

To ensure success as a Data Engineer, you should demonstrate flexibility, creativity, and the capacity to receive and utilize constructive criticism. A formidable Data Engineer will demonstrate unsatiated curiosity and outstanding interpersonal skills.

Essential Responsibilities

  • Design, develop, document, and test advanced data systems that bring together data from disparate sources, making it available to data scientists, analysts, and other users using scripting and/or programming languages (Python, Java, C, etc)
  • Evaluate structured and unstructured datasets utilizing statistics, data mining, and predictive analytics to gain additional business insights
  • Design, develop, and implement data processing pipelines at scale
  • Present programming documentation and design to team members and convey complex information in a clear and concise manner.
  • Extract data from multiple sources, integrate disparate data into a common data model, and integrate data into a target database, application, or file using efficient programming processes.
  • Write and refine code to ensure performance and reliability of data extraction and processing.
  • Communicate with all levels of stakeholders as appropriate, including executives, data modelers, application developers, business users, and customers
  • Participate in requirements gathering sessions with business and technical staff to distill technical requirements from business requests.
  • Partner with clients to fully understand business philosophy and IT Strategy; recommend process improvements to increase efficiency and reliability in ETL development.
  • Collaborate with Quality Assurance resources to debug code and ensure the timely delivery of products.
  • Some of our technologies might include: HDFS, Cassandra, Spark, Java, Scala, Informatica, SQL Server, Oracle, Ab Initio, Kafka.
    Qualifications
    • Bachelor's degree in Data Engineering, Big Data Analytics, Computer Engineering, or related field.
    • At least 3 years of proven experience as a Data Engineer.
    • Expert proficiency in Python, C++, Java, R, and SQL.
    • Familiarity with Hadoop or suitable equivalent.
    • Excellent analytical and problem-solving skills.
    • A knack for independent and group work.
    • Scrupulous approach to duties.
    • Capacity to successfully manage a pipeline of duties with minimal supervision.
    Additional Information

    All your information will be kept confidential according to EEO guidelines.

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