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Senior Business Intelligence Analyst

Introduction

Glu Mobile is now part of the Electronic Arts family, and we love to build free-to-play mobile games. Our titles include Covet Fashion, Design Home, MLB Tap Sports Baseball, and Disney Sorcerer's Arena, to name a few. We are looking for a Senior Business Intelligence Analyst eager to further the team's mission of organizing our data into clear signals that unlock efficient decision-making.

The Role

As a Senior Business Intelligence Analyst, you will be the link between the data we ingest and the teams that depend on that data to make decisions. You will be part of a team charged with ingesting telemetry data and organizing the data into a warehouse.

You will work with Marketing leads to identify opportunities to improve data quality and with Analytics leads on techniques for extracting signal from noisy data. You will work with members of your team on pipelines, data models, and data visualizations. This role is essential to the development of teams across EA Mobile, including Marketing, Finance, and game teams. You will report to the Director, Data Science and Analytics and is based in our San Francisco headquarters location.

Responsibilities:

• Build views and visualizations that measure the health of our marketing campaigns and our games
• Consult with partners
• Troubleshoot data quality issues
• Develop ETL pipelines

Qualifications:

• Passion for games and appreciation for our players
• Excitement for working in a data rich environment
• Experience delivering analytic-driven consulting
• Built dashboards in Tableau, Looker, or similar
• Used SQL to manipulate data in relational databases
• Analyzed data from performance marketing systems

Bonus points:

• Master's Degree in statistics, information systems, or other quantitative fields and two or more years of experience
• Experience building data pipelines, especially using AirFlow
• Experience organizing data using dimensional modeling principles
• Experience working in Unix-like and cloud environments
• Write re-usable code in dynamic programming languages (such Python) or statistical programming environments (such as R or Julia)
• Collaborate on code using Git