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Data Engineer Sports Analytics Jobs (NOW HIRING)

AEG

Data Engineer

Pittsburgh, PA · On-site

$111K - $133K/yr

We're looking for a Data Engineer who wants to own meaningful problems end to end, not just write ... Exposure to cutting-edge work in agentic AI applied to sports analytics. * A team culture that ...

AEG Presents

Data Engineer

Pittsburgh, PA · On-site

$107K - $128K/yr

We're looking for a Data Engineer who wants to own meaningful problems end to end, not just write ... Exposure to cutting-edge work in agentic AI applied to sports analytics. * A team culture that ...

Swish Analytics

Rust Engineer

San Francisco, CA

$170K/yr

... sports analytics data products. We believe that oddsmaking is a challenge rooted in engineering ... mathematics, and sports betting expertise; not intuition. We're looking for team-oriented ...

Swish Analytics

Senior Software Engineer

San Francisco, CA · On-site +1

$150K - $190K/yr

... sports analytics data products. We believe that oddsmaking is a challenge rooted in engineering ... mathematics, and sports betting expertise; not intuition. We're looking for team-oriented ...

AMB Sports & Entertainment

Data Engineer

Atlanta, GA · On-site

$110K - $132K/yr

You'll partner closely with analysts and stakeholders to turn questions into durable data products ... Prior experience in sports, entertainment, media, or live events industries * Familiarity with ...

Swish Analytics

Rust Engineer

San Francisco, CA · On-site +1

$170K/yr

... sports analytics data products. We believe that oddsmaking is a challenge rooted in engineering ... mathematics, and sports betting expertise; not intuition. We're looking for team-oriented ...

AMB Sports + Entertainment

Data Engineer

Atlanta, GA · On-site

$110K - $132K/yr

You'll partner closely with analysts and stakeholders to turn questions into durable data products ... Prior experience in sports, entertainment, media, or live events industries * Familiarity with ...

AMB Sports & Entertainment, LLC

Data Engineer

Atlanta, GA · On-site

$110K - $132K/yr

You'll partner closely with analysts and stakeholders to turn questions into durable data products ... Prior experience in sports, entertainment, media, or live events industries * Familiarity with ...

Swish Analytics

Trading Analyst

San Francisco, CA · Remote

$70K/yr

... sports analytics data products. We believe that oddsmaking is a challenge rooted in engineering, mathematics, and sports betting expertise; not intuition. We're looking for team-oriented individuals ...

Swish Analytics

Trading Analyst

San Francisco, CA · On-site +1

$70K/yr

... sports analytics data products. We believe that oddsmaking is a challenge rooted in engineering, mathematics, and sports betting expertise; not intuition. We're looking for team-oriented individuals ...

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All JobsData Engineer Sports Analytics Jobs

Data Engineer Sports Analytics information

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$44.5K

$129.7K

$177.5K

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

As of Jun 5, 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.

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.

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 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 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.

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 May 2026, with employment types broken down into 95% Full Time, 1% Part Time, 3% Temporary, and 1% Contract. 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.
Machine Learning Engineer

Machine Learning Engineer

Swish Analytics

San Francisco, CA • Remote

$160K/yr

Full-time

Posted 17 days ago

Job description

Swish Analytics is a sports analytics, betting and fantasy startup building the next generation of predictive sports analytics data products. We believe that oddsmaking is a challenge rooted in engineering, mathematics, and sports betting expertise; not intuition. We're looking for team-oriented individuals with an authentic passion for accurate and predictive real-time data who can execute in a fast-paced, creative, and continually-evolving environment without sacrificing technical excellence. Our challenges are unique, so we hope you are comfortable in uncharted territory and passionate about building systems to support products across a variety of industries and enterprise clients.

The Data Science team is hiring an experienced Machine Learning Engineer with a background building machine learning and statistical modeling frameworks from scratch. They can assist with optimizing the different aspects of the modeling process (Data Validation, Data Visualization, Data Stores & Structures, Feature Engineering, Model Training & Evaluation, Deployments) and improving a variety of Swish products. They will know when to “roll your own” and when to outsource a particular step in the modeling process. They will engineer custom solutions to solve complex data-related sports challenges across multiple leagues.

This position is 100% remote

Responsibilities:

  • Design, prototype, implement, evaluate, optimize systems to generate sports datasets and predictions with high accuracy and low latency.

  • Evaluate internal modeling frameworks and tools to optimize data scientist's modeling workflow.

  • Build, test, deploy and maintain production systems.

  • Work closely with DevOps and Data Engineering teams to assist with implementation, optimization and scale workloads on Kubernetes using CI/CD, automation tools and scripting languages.

  • Support maintenance and optimization of cloud-native EDW and ETL solutions.

  • Maintain and promote best practices for software development, including deployment process, documentation, and coding standards.

  • Experience applying large scale data processing techniques to develop scalable and innovative sports betting products.

  • Use extensive experience to build, test, debug, and deploy production-grade components.

  • Experience applying large scale data processing techniques to develop scalable and innovative sports betting products.

  • Participate in development of database structures that fit into the overall architecture of Swish systems

Qualifications:

  • Masters degree in Computer Science, Applied Mathematics, Data Science, Computational Physics/Chemistry or related technical subject area

  • 5+ years of demonstrated experience developing and delivering clean and efficient production code to serve business needs

  • A proven background in quantitative analytics, trading, or engineering is required for this position

  • Demonstrated experience developing data science modeling systems and infrastructure at scale

  • Experience with Python and exposure to modern machine learning frameworks

  • Proficient in SQL; experience with MySQL

  • Background and/or interest in Rust preferred

  • Affinity for teamwork and collaboration with others to solve problems, share knowledge, and provide feedback

  • Strong communication skills when discussing technical concepts with technical and non-technical colleagues

Base salary: starting at $160,000 base plus bonus potential

Swish Analytics is an Equal Opportunity Employer. All candidates who meet the qualifications will be considered without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, pregnancy status, genetic, military, veteran status, marital status, or any other characteristic protected by law. The position responsibilities are not limited to the responsibilities outlined above and are subject to change. At the employer’s discretion, this position may require successful completion of background and reference checks.