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Role Overview
We are seeking a hands-on Engineering Manager to join EA’s Data & Insights – Enterprise Data Engineering (EDE) team, the organization responsible for delivering the central data platform that powers analytics and data solutions across all EA games. This role blends strong technical leadership with deep data engineering expertise to build scalable, reliable, and high-impact data systems that support the entire enterprise.
The ideal candidate has extensive experience designing and operating large-scale data platforms, leading complex data engineering initiatives, and working across distributed computing, batch and real-time data processing, and modern lakehouse architectures. In this role, you will lead and grow a high-performing team of data engineers while remaining actively engaged in architecture, design, coding, and troubleshooting.
You will collaborate closely with game teams, product partners, analytics groups, and infrastructure teams to translate business needs into robust technical solutions. You will drive roadmap execution, establish best practices, ensure data quality and reliability, and foster a culture of innovation, ownership, and continuous improvement. Mastery of technologies such as Python/Java, SQL, Spark, Kafka, Airflow, Snowflake, AWS, Iceberg, and distributed data systems is essential.
This role is ideal for a hands-on technical leader who is passionate about building world-class data platforms at scale and enabling data-driven experiences across all EA titles.
Key Responsibilities
Lead, mentor, and develop a high-performing engineering team through coaching, feedback, and career development.
Remain hands-on with architecture, design, coding, and technical decisions—contributing directly when needed.
Drive complex data engineering initiatives across batch, streaming, and lakehouse ecosystems (e.g., Spark, Kafka, Iceberg).
Translate business requirements into scalable technical architectures and data solutions.
Collaborate with product, analytics, and platform teams to define roadmaps and deliver high-quality solutions on schedule.
Establish and uphold engineering best practices in code quality, CI/CD, observability, data quality, and operational reliability.
Recruit, onboard, and grow engineering talent while fostering a culture of ownership, innovation, and continuous improvement.
Manage stakeholder communication, providing clear expectations and transparent updates on progress, risks, and mitigation plans.
Qualifications
Bachelor’s or Master’s degree in Computer Science, Engineering, or equivalent degree
8+ years of professional experience as a hands-on engineer and technical leader managing multiple projects.
5+ years of experience in data platforms, data engineering, or a similar role.
Strong hands-on programming experience in Python or Java, with the ability to contribute to production code.
Extensive experience with ETL orchestration and workflow tools (e.g., Airflow), data reliability frameworks, and SQL.
Deep understanding of distributed systems and modern data technologies (e.g., Spark, Presto, Kafka, Flink, Iceberg).
Proficiency with cloud platforms (AWS, GCP) and enterprise-scale data environments (Snowflake, Spark, Trino, Databricks).
Hands-on experience designing scalable data pipelines across both batch and real-time processing architectures.
Familiarity with data lake formats, metadata/catalog services (Iceberg, Delta, Glue Catalog), and object storage systems (S3, GCS).
Strong system design capabilities and the ability to apply AI/ML-driven approaches to enhance data workflows when appropriate.