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Data Engineer

Sunnyvale, TX, United States

Live, first seen by us 20 days ago
Pay
$162,300–182,300/year — pay source
Fanatics is building a leading global digital sports platform. We ignite the passions of global sports fans and maximize the presence and reach for our hundreds of sports partners globally by offering products and services across Fanatics Commerce, Fanatics Collectibles, and Fanatics Betting & Gaming, allowing sports fans to Buy, Collect, and Bet. Through the Fanatics platform, sports fans can buy licensed fan gear, jerseys, lifestyle and streetwear products, headwear, and hardgoods; collect physical and digital trading cards, sports memorabilia, and other digital assets; and bet as the company builds its Sportsbook and iGaming platform. Fanatics has an established database of over 100 million global sports fans; a global partner network with approximately 900 sports properties, including major national and international professional sports leagues, players associations, teams, colleges, college conferences and retail partners, 2,500 athletes and celebrities, and 200 exclusive athletes; and over 2,000 retail locations, including its Lids retail stores. Our more than 22,000 employees are committed to relentlessly enhancing the fan experience and delighting sports fans globally. Design, build, and maintain scalable data pipelines using orchestration frameworks such as Airflow and Dagster to support reliable data ingestion and transformation across multiple upstream systems 35%; Develop and manage a centralized data platform that integrates diverse data sources (e.g., APIs, databases, third-party systems), ensuring data quality, consistency, and availability for downstream consumption 20%; Implement robust data modeling and transformation processes (ETL/ELT) to structure raw data into curated datasets optimized for analytics and business use cases 15%; Enable self-service data access by building data services, semantic layers, and AI-powered tools (e.g., agents, query interfaces) that allow business users to easily explore and consume data 10%; Collaborate with cross functional teams (data scientists, analysts, and business stakeholders) to define data requirements and ensure scalable, production-grade data solutions 10%; Design and maintain monitoring, logging, and alerting systems to ensure pipeline reliability, performance, and data integrity 5%; Apply software engineering best practices (CI/CD, version control, testing) to develop and deploy data infrastructure and pipeline code in a cloud-based environment 5%. Up to 5% domestic travel may be required for internal meetings. Partial telecommuting permitted; on-site at 11601 Wilshire Blvd., Los Angeles, CA 90025 when not telecommuting. Salary: $162,300 - $182,300 per year. MINIMUM REQUIREMENTS: Bachelor’s Degree or U.S. equivalent in Computer Science, Computer Engineering, Engineering Management, or a related field, plus 4 years of professional experience as a Data Scientist, Data Analyst, or any occupation, job title, or position performing data-driven software engineering and analytics development.
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What you’ll work on

Full posting
  • Design, build and maintain scalable data pipelines with Airflow and Dagster

  • Develop and manage a centralized data platform that integrates diverse data sources

  • Model and transform raw data into curated datasets for analytics (ETL/ELT)

  • Build data services, semantic layers and AI-powered tools for self-service data access

  • Design monitoring, logging and alerting to keep pipelines reliable

From the employer’s posting
Design, build, and maintain scalable data pipelines using orchestration frameworks such as Airflow and Dagster
Develop and manage a centralized data platform that integrates diverse data sources (e.g., APIs, databases, third-party systems)
Implement robust data modeling and transformation processes (ETL/ELT) to structure raw data into curated datasets
Enable self-service data access by building data services, semantic layers, and AI-powered tools
Design and maintain monitoring, logging, and alerting systems to ensure pipeline reliability, performance, and data integrity

About Fanatics Collectibles

Fanatics is building a leading global digital sports platform.

In the employer’s words · Read in context

Apply at Fanatics Collectibles

Posting record

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Status in our records
Live
First seen by us
Oct 15, 202620 days ago
Recorded sightings
40
Last seen by us
Nov 4, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Pay

In line with similar jobs

$162K–$182K against $127K–$190K, the middle half of what similar US postings state.

From 2,133 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 20

Similar jobs usually come down between day 5 and day 54.

From 10,733 similar postings that came down. Coming down is not always a hire.

Fanatics Collectibles is hiring

5 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Hiring is picking up
  • Takes jobs down at a usual pace
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • SQL
  • AWS
  • Looker
  • Tableau
  • Airflow
  • Dagster
  • pandas
  • PySpark
Where the posting names them
MINIMUM REQUIREMENTS: Bachelor’s Degree or U.S. equivalent in Computer Science, Computer Engineering, Engineering Management, or a related field, plus 4 years of professional experience as a Data Scientist, Data Analyst, or any occupation, job title, or position performing data-driven software engineering and analytics development. Must also have experience in the following: 4 years of professional experience collaborating with cross functional stakeholders (including business, product, engineering, and data teams) to translate business requirements into scalable analytical solutions; 4 years of professional experience applying software engineering best practices to analytical codebases, including version control (Git), peer code reviews, and modular code development; 3 years of professional experience writing complex SQL queries and performing data mining across large relational or cloud-based data warehouse environments; 3 years of professional experience designing and developing data pipelines using Python (including Pandas and PySpark) and ETL processes to transform and prepare large datasets for analytical use; 3 years of professional experience developing and optimizing data models, custom datasets, and data structures to support evolving analytical and reporting needs; 3 years of professional experience designing and developing business intelligence dashboards and automated reporting solutions SQL and visualization tools (including Tableau, QuickSight, or Looker) to support KPI tracking and executive reporting; 3 years of professional experience maintaining and optimizing cloud-based data solutions within AWS environments to ensure performance, reliability, and scalability; 3 years of professional experience conducting statistical analyses, including hypothesis testing, regression analysis, and product experimentation to inform business decision-making. CONTACT: Apply online at fanaticsinc.com/careers or email resume to: WorkWithFanatics@FanaticsInc.com. Must specify Ad Code AMKM in subject line. #LI-DNI #LI-DNP
Fanatics is building a leading global digital sports platform. We ignite the passions of global sports fans and maximize the presence and reach for our hundreds of sports partners globally by offering products and services across Fanatics Commerce, Fanatics Collectibles, and Fanatics Betting & Gaming, allowing sports fans to Buy, Collect, and Bet. Through the Fanatics platform, sports fans can buy licensed fan gear, jerseys, lifestyle and streetwear products, headwear, and hardgoods; collect physical and digital trading cards, sports memorabilia, and other digital assets; and bet as the company builds its Sportsbook and iGaming platform. Fanatics has an established database of over 100 million global sports fans; a global partner network with approximately 900 sports properties, including major national and international professional sports leagues, players associations, teams, colleges, college conferences and retail partners, 2,500 athletes and celebrities, and 200 exclusive athletes; and over 2,000 retail locations, including its Lids retail stores. Our more than 22,000 employees are committed to relentlessly enhancing the fan experience and delighting sports fans globally. Design, build, and maintain scalable data pipelines using orchestration frameworks such as Airflow and Dagster to support reliable data ingestion and transformation across multiple upstream systems 35%; Develop and manage a centralized data platform that integrates diverse data sources (e.g., APIs, databases, third-party systems), ensuring data quality, consistency, and availability for downstream consumption 20%; Implement robust data modeling and transformation processes (ETL/ELT) to structure raw data into curated datasets optimized for analytics and business use cases 15%; Enable self-service data access by building data services, semantic layers, and AI-powered tools (e.g., agents, query interfaces) that allow business users to easily explore and consume data 10%; Collaborate with cross functional teams (data scientists, analysts, and business stakeholders) to define data requirements and ensure scalable, production-grade data solutions 10%; Design and maintain monitoring, logging, and alerting systems to ensure pipeline reliability, performance, and data integrity 5%; Apply software engineering best practices (CI/CD, version control, testing) to develop and deploy data infrastructure and pipeline code in a cloud-based environment 5%. Up to 5% domestic travel may be required for internal meetings. Partial telecommuting permitted; on-site at 11601 Wilshire Blvd., Los Angeles, CA 90025 when not telecommuting. Salary: $162,300 - $182,300 per year. MINIMUM REQUIREMENTS: Bachelor’s Degree or U.S. equivalent in Computer Science, Computer Engineering, Engineering Management, or a related field, plus 4 years of professional experience as a Data Scientist, Data Analyst, or any occupation, job title, or position performing data-driven software engineering and analytics development.

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About the role

We file this job under Data Engineer, by the work the posting describes.

Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.

Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.

An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.

US government figures for database architects

Median yearly pay, May 2025
$139,500
Expected change, 2025 to 2035
9.4% more jobsagainst 3.5% for all jobs

The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.

Job description

View original posting ↗

About Us

Fanatics is building a leading global digital sports platform. We ignite the passions of global sports fans and maximize the presence and reach for our hundreds of sports partners globally by offering products and services across Fanatics Commerce, Fanatics Collectibles, and Fanatics Betting & Gaming, allowing sports fans to Buy, Collect, and Bet. Through the Fanatics platform, sports fans can buy licensed fan gear, jerseys, lifestyle and streetwear products, headwear, and hardgoods; collect physical and digital trading cards, sports memorabilia, and other digital assets; and bet as the company builds its Sportsbook and iGaming platform. Fanatics has an established database of over 100 million global sports fans; a global partner network with approximately 900 sports properties, including major national and international professional sports leagues, players associations, teams, colleges, college conferences and retail partners, 2,500 athletes and celebrities, and 200 exclusive athletes; and over 2,000 retail locations, including its Lids retail stores. Our more than 22,000 employees are committed to relentlessly enhancing the fan experience and delighting sports fans globally. 

 

Design, build, and maintain scalable data pipelines using orchestration frameworks such as Airflow and Dagster to support reliable data ingestion and transformation across multiple upstream systems 35%; Develop and manage a centralized data platform that integrates diverse data sources (e.g., APIs, databases, third-party systems), ensuring data quality, consistency, and availability for downstream consumption 20%; Implement robust data modeling and transformation processes (ETL/ELT) to structure raw data into curated datasets optimized for analytics and business use cases 15%; Enable self-service data access by building data services, semantic layers, and AI-powered tools (e.g., agents, query interfaces) that allow business users to easily explore and consume data 10%; Collaborate with cross functional teams (data scientists, analysts, and business stakeholders) to define data requirements and ensure scalable, production-grade data solutions 10%; Design and maintain monitoring, logging, and alerting systems to ensure pipeline reliability, performance, and data integrity 5%; Apply software engineering best practices (CI/CD, version control, testing) to develop and deploy data infrastructure and pipeline code in a cloud-based environment 5%. Up to 5% domestic travel may be required for internal meetings. Partial telecommuting permitted; on-site at 11601 Wilshire Blvd., Los Angeles, CA 90025 when not telecommuting. Salary: $162,300 - $182,300 per year.

MINIMUM REQUIREMENTS: Bachelor’s Degree or U.S. equivalent in Computer Science, Computer Engineering, Engineering Management, or a related field, plus 4 years of professional experience as a Data Scientist, Data Analyst, or any occupation, job title, or position performing data-driven software engineering and analytics development.

Must also have experience in the following: 4 years of professional experience collaborating with cross functional stakeholders (including business, product, engineering, and data teams) to translate business requirements into scalable analytical solutions; 4 years of professional experience applying software engineering best practices to analytical codebases, including version control (Git), peer code reviews, and modular code development; 3 years of professional experience writing complex SQL queries and performing data mining across large relational or cloud-based data warehouse environments; 3 years of professional experience designing and developing data pipelines using Python (including Pandas and PySpark) and ETL processes to transform and prepare large datasets for analytical use; 3 years of professional experience developing and optimizing data models, custom datasets, and data structures to support evolving analytical and reporting needs; 3 years of professional experience designing and developing business intelligence dashboards and automated reporting solutions SQL and visualization tools (including Tableau, QuickSight, or Looker) to support KPI tracking and executive reporting; 3 years of professional experience maintaining and optimizing cloud-based data solutions within AWS environments to ensure performance, reliability, and scalability; 3 years of professional experience conducting statistical analyses, including hypothesis testing, regression analysis, and product experimentation to inform business decision-making.

CONTACT: Apply online at fanaticsinc.com/careers or email resume to: WorkWithFanatics@FanaticsInc.com. Must specify Ad Code AMKM in subject line. #LI-DNI #LI-DNP

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