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Description & Requirements
Central Technology is the force multiplier, accelerating creative opportunity and progress at EA. We're a world-class community of technologists, innovators, strategists, and orchestrators transforming interactive entertainment. Together, we power the platforms, AI-driven tools, live services, and infrastructure that ensure global scale, secure player experiences, and unlock bold new possibilities.
The Data & Insights (D&I) team transforms data into actionable insights that power EA. We guide strategy and governance, build data and AI solutions, and ensure personalization experimentation and analytics; partnering across teams to improve decisions and create more meaningful player experiences.
Within D&I, the Enterprise Data & Insights Engineering (EDIE) team focuses on building the foundational data systems and platforms that power EA's lifecycle management capabilities at scale. As a Software Engineer, you will develop ETL pipelines, ensure data quality, and use AI/GenAI tools to improve engineering efficiency. You will report to the Data Platform Engineering team manager.
Responsibilities:
You will build solutions serving billions of player profiles, forming the foundation for lifecycle management services such as Unified Messaging, Segmentation, and Recommendations.
You will develop quality assurance tools to ensure data accuracy, freshness, and reliability.
You will design and implement ETL solutions to support both batch and real-time data processing.
You will work with our internal customers to design, and implement new automated workflows
Qualifications:
3+ years of experience as a software engineer
3+ years of programming experience in Java/Python and SQL expertise
Cloud platforms (AWS, GCP)
Data warehouses (Snowflake, Redshift, BigQuery)
Experience with NoSQL databases (Cassandra or ScyllaDB)
Experience with distributed processing (Spark, Trino) and streaming technologies (Kafka, Flink, and Spark Streaming)
Experience with Airflow, Git/CI/CD, and containerization tools (Docker, Kubernetes)
Experience with backend frameworks (Spring Boot or Node.js)
Frontend technologies (React, Angular, HTML and CSS)