Data Engineer

Fanatics Collectibles • Sunnyvale, TX

10d • $162,300 - $182,300 • Hybrid

About The Position

Fanatics is building a global digital sports platform spanning commerce, collectibles, and betting and gaming. The Data Engineer will design, build, and maintain scalable data pipelines and a centralized data platform that integrates data from multiple upstream systems. The role will develop data models and ETL/ELT transformations, and make data easier for business users to access through data services, semantic layers, and AI-powered tools. It will also work with data scientists, analysts, and business stakeholders to define requirements and deliver reliable production-grade data solutions.

The position includes designing monitoring, logging, and alerting systems and applying software engineering practices to data infrastructure and pipeline code in a cloud environment. Up to 5% domestic travel may be required for internal meetings. Partial telecommuting is permitted; the employee works onsite at 11601 Wilshire Blvd., Los Angeles, CA 90025 when not telecommuting. The annual salary range is $162,300–$182,300.

Requirements

• Bachelor’s degree or U.S. equivalent in Computer Science, Computer Engineering, Engineering Management, or a related field.
• At least 4 years of professional experience as a Data Scientist, Data Analyst, or in another role performing data-driven software engineering and analytics development.
• 4 years of experience collaborating with cross-functional business, product, engineering, and data stakeholders to translate business requirements into scalable analytical solutions.
• 4 years of experience applying software engineering best practices to analytical codebases, including Git, peer code reviews, and modular code development.
• 3 years of experience writing complex SQL queries and performing data mining across large relational or cloud-based data warehouse environments.
• 3 years of 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 experience developing and optimizing data models, custom datasets, and data structures for evolving analytical and reporting needs.
• 3 years of experience designing and developing business intelligence dashboards and automated reporting using SQL and visualization tools such as Tableau, QuickSight, or Looker.
• 3 years of experience maintaining and optimizing cloud-based data solutions in AWS for performance, reliability, and scalability.
• 3 years of experience conducting statistical analyses, including hypothesis testing, regression analysis, and product experimentation, to inform business decisions.

Responsibilities

• Design, build, and maintain scalable data pipelines using orchestration frameworks such as Airflow and Dagster to support reliable ingestion and transformation across upstream systems.
• Develop and manage a centralized data platform integrating sources such as APIs, databases, and third-party systems while ensuring data quality, consistency, and availability.
• Implement data modeling and ETL/ELT transformations to produce curated datasets for analytics and business use cases.
• Enable self-service data access through data services, semantic layers, and AI-powered tools such as agents and query interfaces.
• Collaborate with data scientists, analysts, and business stakeholders to define data requirements and deliver scalable, production-grade data solutions.
• Design and maintain monitoring, logging, and alerting systems for pipeline reliability, performance, and data integrity.
• Apply software engineering practices, including CI/CD, version control, and testing, to develop and deploy data infrastructure and pipeline code in a cloud environment.
• Travel domestically up to 5% for internal meetings, if required.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level