Data Engineer

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 2500 athletes and celebrities and 200 exclusive athletes; and over 2000 retail locations including its Lids retail stores. Our more than 22000 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: $162300 - $182300 per year.

MINIMUM REQUIREMENTS: Bachelors 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 or email resume to: Must specify Ad Code AMKM in subject line. #LI-DNI #LI-DNP

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Required Experience:

IC