Electronic Arts

Senior Analyst, Fan Care

Location: Hybrid in Vancouver

Reports to: Manager, AI, Tools, & Automated Solutions

AI, Tools, & Automated Solutions

At our core, Electronic Arts is a game maker connecting hundreds of millions of players globally to some of the world’s greatest games. The AI, Tools, & Automated Solutions team supports EA’s global Fan Care organization by building scalable, governed data foundations and automation infrastructure that power operational decision-making.

We focus on delivering reliable, repeatable data pipelines, warehouse models, and reporting solutions that enable operational excellence and support AI-ready data ecosystems.

The Role

As a Senior Analyst within AI, Tools, & Automated Solutions, you will design and build scalable data pipelines, warehouse models, and governed BI dashboards that support global Fan Care operations.

This role is heavily focused on ETL development, data modeling, and backend data architecture rather than exploratory product analytics or experimentation. You will translate business requirements into robust technical solutions that scale and serve as trusted sources of operational truth.

Responsibilities

• Design, develop, and maintain scalable ETL pipelines and transformation workflows
  

• Build and maintain data models within cloud data warehouse environments
  

• Develop governed datasets that ensure metric consistency and reliability
  

• Build dashboards and reporting solutions to support operational performance monitoring
  

• Implement data validation, quality checks, and documentation standards
  

• Optimize and refactor existing pipelines for performance and scalability
  

• Partner with cross-functional stakeholders to translate requirements into sustainable data solutions

Required Qualifications

• Bachelor’s degree in analytics, computer science, statistics, engineering, or related field
  

• 5+ years of experience in analytics, business intelligence, or data engineering–focused roles
  

• Advanced SQL with strong experience transforming and modeling large-scale datasets
  

• Hands-on experience building and owning ETL pipelines
  

• Experience working with cloud data warehouses (e.g., Redshift, Snowflake, BigQuery, Azure)
  

• Experience with data visualization tools such as Tableau, Power BI, or Looker

Core Skills and Experience

• Strong data modeling and warehouse architecture fundamentals
  

• Experience building governed, scalable datasets
  

• Knowledge of transformation frameworks such as dbt (preferred)
  

• Ability to implement data quality checks and validation processes
  

• Clear communication with technical and non-technical stakeholders
  

• Experience working with large operational or behavioral datasets