Electronic Arts

EA SPORTS is one of the leading sports entertainment brands in the world, with top-selling videogame franchises, award-winning interactive technology, fan programs, and cross-platform digital experiences. EA SPORTS creates connected experiences that ignite the emotion of sport through industry-leading sports video games, including Madden NFL football, EA Sports FC, NHL® hockey, NBA LIVE basketball, and EA SPORTS UFC.

At the heart of EA SPORTS is the FC franchise. EA SPORTS FC is the world's #1 best-selling video game with over 200M engaged players across multiple platforms, including console, PC, and mobile. Innovation, passion, and teamwork are at the heart of everything we do. With studios in Vancouver, Bucharest, and Cologne, we're looking for the brightest talent, so we can continue to create experiences that connect with millions of hearts and minds the world over.

Reporting to the Senior Data Science Manager, we are 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. The ideal candidate thrives in a dynamic environment, balancing hands-on development with architectural leadership. You will be responsible for creating robust data models, managing scalable infrastructure, and collaborating directly with stakeholders to translate complex requirements into resilient, high-performance data solutions.

Your Responsibilities:

• Data Architecture & Modeling: Lead the design and implementation of robust, scalable data architectures and conceptual/logical data models that support complex analytical requirements and future business growth.

• End-to-End Pipeline Ownership: 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.

• Technical Strategy & Execution: Address sophisticated data engineering challenges including data ingestion, storage strategies, and reliability by building modular, maintainable, and highly available systems.

• System Maintenance & Scalability: Oversee the deployment and optimization of batch and real-time processing frameworks, ensuring data quality, performance tuning, and robust alerting mechanisms.

• Cross-Functional Communication: 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.

Your Qualifications

We are seeking a highly skilled Data Engineer with 4-6+ years of relevant experience, demonstrating a sophisticated blend of technical engineering expertise and strategic architectural leadership.

• Strategic Data Architecture: Proven expertise in designing resilient data architectures and conceptual/logical models that accommodate complex analytical needs and scale with future business growth.

• Advanced Database Systems: Deep technical proficiency in architecting, managing, and optimizing high-performance SQL and No-SQL database environments.

• Big Data Ecosystem Expertise: Extensive experience building and operating distributed systems leveraging technologies such as Trino, Spark, and Kafka.

• Software Engineering Excellence: Advanced programming skills in Python, C#, or Scala, with a dedicated focus on developing clean, modular, and production-grade code.

• Cloud Infrastructure & Scaling: Hands-on experience deploying and scaling data infrastructure within cloud environments, with a strong preference for AWS.

• Resilient Pipeline Orchestration: Proven ability to engineer and maintain robust ETL/ELT pipelines and data workflows using industry-standard tools like Airflow.

• AI/BI & Data Governance: 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.