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Data Engineer Sports Analytics Jobs (NOW HIRING)

Swish Analytics

Sports Data Analyst

San Francisco, CA

... 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 ...

Swish Analytics

Sports Data Analyst

San Francisco, CA · On-site +1

... 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 ...

PFF

Senior Data Engineer

$120K - $160K/yr

About PFF PFF is a leading sports analytics company that transforms complex football data into ... Act as a subject matter expert, guiding the engineering team on best practices for data modeling ...

Swish Analytics

Basketball Data Scientist

San Francisco, CA · On-site +1

$130K/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

NFL Data Scientist

San Francisco, CA · On-site +1

$140K/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

Tennis Data Scientist

San Francisco, CA · On-site +1

$135K - $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 individuals ...

Swish Analytics

NFL Data Scientist

San Francisco, CA · On-site

$140K/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

Tennis Data Scientist

San Francisco, CA · On-site

$135K - $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 individuals ...

Inizio Partners Corp

AWS Data Engineer

New York, NY · On-site

$125K - $150K/yr

We are seeking a seasoned Data Engineer to join our Sports Analytics & Engineering Practice. This role is pivotal in shaping and implementing our client's vision for a cutting-edge, cloud-native data ...

Lorven Technologies

AWS Data Engineer

$117K - $140K/yr

We are seeking a seasoned Data Engineer to join our Sports Analytics & Engineering Practice. This role is pivotal in shaping and implementing our client's vision for a cutting-edge, cloud-native data ...

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 ...

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

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 ...

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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.
Sports Data Analyst

Sports Data Analyst

Swish Analytics

San Francisco, CA

Full-time

Posted 8 days ago

Job description

Company 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 consumer/enterprise clients.

Duties:

  • Work closely with Data Scientists and Engineers to diagnose and treat data pipeline integrity issues

  • Detect data inaccuracies such as missing, out of range or otherwise incorrect on-field data

  • Source origins of data inaccuracies through data pipeline dependencies and python code base

  • Define data validation tests to flag future game errors

  • Research accurate roster active statuses, primary positions and game participation

  • Validate data changes after logic updates

  • Production model feature deep dives to explain project market lines

  • Clearly document findings

  • Develop intimate familiarity with existing databases and construct metadata references

  • With guidance, support lead Data Scientists in feature development and model analysis

Requirements:

  • Bachelor's Degree in Computer Science, Data Science or similar major

  • Minimum of 1 year of experience in football data analysis

  • Deep knowledge of football, basketball or baseball; including roster compositions of professional and college teams, general gameplay strategies, and typical in-game scenarios

  • Data Extraction, Wrangling and Analysis in Python

  • Strong SQL querying skills

  • Attention to detail

Preferred:

  • Strong Python data management programming skills

  • Data Visualization experience with a user application like Streamlit

  • Deep knowledge of a second sport including football, basketball, baseball, hockey or tennis

  • Exposure to the data science process and tech stack

  • Anomaly Detection Techniques

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.