Data Engineer

Fanatics; Sunnyvale (TX); Hybrid; USD 162,000 - 182,000; Full time

Job summary

Fanatics is seeking a data scientist to design, build, and maintain scalable data pipelines and a centralized data platform that ingests data from diverse sources for analytics.

You will implement ETL/ELT processes, enable self-service data access with data services and AI-powered tools, and collaborate with cross-functional teams to deliver reliable insights for business decisions while following CI/CD and cloud best practices.

Qualifications

• 4 years of professional experience collaborating with cross functional stakeholders 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

Responsibilities

• Design, build, and maintain scalable data pipelines via Airflow and Dagster
• Develop a centralized data platform integrating diverse sources for analytics
• Implement ETL/ELT to structure raw data into curated datasets
• Enable self-service data access with data services, semantic layers, and AI-powered tools
• Collaborate with data scientists, analysts, and stakeholders to define data requirements
• Design and maintain monitoring, logging, and alerting for pipeline reliability
• Apply CI/CD and other software engineering practices to data infrastructure in the cloud

Skills

Cross-functional collaboration

Software engineering best practices

SQL

Python (Pandas, PySpark)

ETL/ELT design

Data modeling

BI dashboards and automated reporting

AWS cloud data solutions

Statistics for experimentation

Education

Bachelor’s Degree in CS/CE/Eng Mgmt or related field

Tools

Git

Tableau

Looker

QuickSight

Power BI

SQL-based data warehouses

PySpark

Pandas

Job description

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

Fanatics will never ask candidates for money, banking information, or other sensitive personal information as part of the interview process. If you receive a suspicious message claiming to be from Fanatics recruiting, please do not respond and report it here.