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Data Engineer Sports Analytics Jobs (NOW HIRING)

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 ...

Pantheon Data

Data Engineer

Washington, DC · On-site

$80K - $120K/yr

Collaborate with analysts, data scientists, and stakeholders. Required Skills and Experience * Bachelor's degree in Data Engineering, Computer Science, Software Engineering, or related field. * AWS ...

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 ...

Pantheon Data

Data Engineer

Washington, DC · On-site

$80K - $120K/yr

Collaborate with analysts, data scientists, and stakeholders. Required Skills and Experience * Bachelor's degree in Data Engineering, Computer Science, Software Engineering, or related field. * AWS ...

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 ...

US Mobile

Analytics Data Engineer

New York, NY

$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 ...

US Mobile

Analytics Data Engineer

New York, NY

$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 ...

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 ...

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 ...

Alliance Credit Union

Data Engineer

Lubbock, TX · On-site

$78K - $90K/yr

... and predictive analytics to strengthen our world-class analytics capabilities and deliver ... The Data Engineer II plays an advanced individual contributor role in supporting these efforts by ...

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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 Jul 20, 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.

How much do NFL data analysts make?

NFL data analysts typically earn between $60,000 and $100,000 annually, depending on experience, education, and the level of responsibility. These roles often require proficiency in data analysis tools, programming languages, and sports analytics knowledge. Salaries can vary based on the organization and geographic location.

Can a data analyst work in sports?

A data analyst can work in sports by analyzing player performance, game statistics, and team data to support decision-making. Skills in data visualization, statistical analysis, and tools like SQL and Python are commonly used in sports analytics roles. Transitioning to sports analytics often requires knowledge of the sport and relevant data sources.

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.

Do NFL teams hire data analysts?

Yes, NFL teams often hire data analysts and data engineers to analyze player performance, game strategies, and injury data. These roles typically require skills in data management, statistical analysis, and familiarity with sports analytics tools like R or Python. Data professionals help teams make data-driven decisions to improve performance and competitiveness.

Is 40 too late for data science?

For a Data Engineer in sports analytics, starting a career at 40 is feasible, especially with relevant skills in programming, data management, and analytics tools. Many professionals transition into data roles later in life, and experience in related fields can be an advantage. Continuous learning and certifications can help accelerate entry into the field regardless of age.
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Data Engineer Sports Analytics jobs near you

Data Engineer

Tredence Analytic

Chicago, IL • On-site

$118K - $141K/yr

Full-time

Re-posted 4 hours 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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