Software Engineer III (Data & Insights)

Join Electronic Arts' central engineering team to build the next-generation Lifecycle Management (LCM) Experimentation & Analytics Platform. This platform supports live services across 20+ world-class game studios and millions of daily active players.

As a Software Engineer III - EA Enterprise Intelligence, you will work at the intersection of Software Engineering, Data Science, Data Analytics, and Data Engineering. Your role involves transforming cutting-edge statistical methodologies, experimentation designs, and advanced analytics frameworks into scalable, robust, and reusable platform services.

Responsibilities:

• Build configuration dashboards for game studio teams to launch and evaluate experiments independently.
• Develop and maintain low-latency APIs and microservices for real-time experiment assignment and player targeting at scale.
• Develop contextual analytics systems for batch and real-time processing pipelines.
• Partner with DS, DA, and DE teams to platformize, package, and automate statistical or Machine Learning methodologies.
• Standardize behavioral event schemas, configuration models, and metadata contracts across diverse game titles.
• Promote the value of the LCM platform by providing in-depth data insights into players' engagement with content across live channels.

Qualifications:

• Master's degree or foreign degree equivalent in Computer Science, Electrical Engineering, or a related field.
• 3+ years of experience in software development building data-intensive systems, distributed backend services, or platform APIs.
• Strong experience collaborating with Data Science, Data Analytics, or Machine Learning teams.
• Solid conceptual understanding of A/B testing, hypothesis testing, and core statistical mechanisms.
• Expertise in Python and at least one compiled language (such as Java, Go, or Scala), along with advanced SQL skills.
• Experience with distributed data frameworks and modern Lakehouse/Data Warehouse solutions.
• Familiarity with cloud services (AWS preferred), containerization (Docker/Kubernetes), and pipeline workflow orchestrators (like Airflow).
• Strong cross-functional collaboration and communication across regions/time zones.