Data Engineer - EA Sports FC

Electronic Arts is seeking a seasoned Data Engineer to design and architect high-impact, end-to-end data pipelines that deliver actionable business insights. As a key member of our multidisciplinary team, you will bridge the gap between complex technical engineering and strategic business objectives.

Responsibilities:

• Lead the design and implementation of robust, scalable data architectures and conceptual/logical data models that support complex analytical requirements and future business growth.
• Own the entire data lifecycle, from initial requirement gathering to the deployment and maintenance of high-performance, resilient ETL/ELT pipelines and data processing workflows.
• Address sophisticated data engineering challenges including data ingestion, storage strategies, and reliability by building modular, maintainable, and highly available systems.
• Oversee the deployment and optimization of batch and real-time processing frameworks, ensuring data quality, performance tuning, and robust alerting mechanisms.
• Serve as a bridge between technical and business teams; clearly translate complex architectural trade-offs, technical designs, and project constraints to non-technical stakeholders to ensure alignment on strategic data initiatives.

Qualifications:

• 4-6+ years of relevant experience as a Data Engineer.
• Proven expertise in designing resilient data architectures and conceptual/logical models that accommodate complex analytical needs and scale with future business growth.
• Deep technical proficiency in architecting, managing, and optimizing high-performance SQL and No-SQL database environments.
• Extensive experience building and operating distributed systems leveraging technologies such as Trino, Spark, and Kafka.
• Advanced programming skills in Python, C#, or Scala, with a dedicated focus on developing clean, modular, and production-grade code.
• Hands-on experience deploying and scaling data infrastructure within cloud environments, with a strong preference for AWS.
• Proven ability to engineer and maintain robust ETL/ELT pipelines and data workflows using industry-standard tools like Airflow.
• Experience delivering AI-driven insights and self-service intelligence via Alation AI, Databricks AI/BI, or similar services, while championing data cataloging and governance to ensure high-quality, actionable data.