Data Engineer - EA Sports FC
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 Data Engineer to implement and maintain high-impact, end-to-end data pipelines that deliver actionable business insights. As a key member of our multidisciplinary team, you will support the bridge between technical engineering and strategic business objectives. The ideal candidate thrives in a dynamic environment, balancing hands-on development with collaborative execution. You will be responsible for implementing robust data models, maintaining scalable infrastructure, and collaborating with stakeholders to translate requirements into resilient, high-performance data solutions.
Your Responsibilities:
Data Modeling & Implementation: Design and implement robust, scalable 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.
Collaborative Communication: Work across technical and business teams to communicate technical designs and project constraints, ensuring alignment on data initiatives and the delivery of high-quality pipelines.
Your Qualifications
We are seeking a skilled Data Engineer with 2-4+ years of relevant experience, demonstrating a strong technical engineering foundation and a focus on reliable data delivery.
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.