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Staff Data Engineer - League of Legends
Riot Games · Los Angeles, CA
Publicada em 05/10/2026
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Riot’s Data Engineers harness petabytes of data and state-of-the-art processing technologies to build products that elevate the player experience at massive scale.
As a Staff Data Engineer on the League of Legends Data Engineering team, you will collaborate with product managers, analysts, and engineers to ensure our data is reliable, performant, and scalable. You will design and champion data standards to ensure our systems grow with our player base. This role will be based out of our Los Angeles headquarters.
Responsibilities:
Design and lead the implementation of architectures that support advanced analytics and machine learning models
Develop scalable, medallion-oriented data models that cater to both current and future needs where data volume grows significantly.
Design and implement ETL processes and data integration strategies to handle diverse data sources and formats
Liaison between our team, the League of Legends team, and service teams as well as central platform teams to understand their needs and provide solutions
Analyze existing systems for bottlenecks and inefficiencies, and implement solutions to optimize data flow and processing for high-volume, complex datasets
Lead initiatives in data governance, data quality, and metadata management that ensure data accuracy, consistency, and security
Explore and evaluate new technologies, tools, and data management practices to enhance the capabilities of the data platform
Collaborate closely with machine learning engineers and analysts, providing them with the data required for complex analytics, machine learning models, and data exploration
Communicate complex data concepts and the value of data projects to stakeholders at all levels of the organization, influencing data-driven decision-making and strategy
On-call responsibility for production systems powering critical product observability and machine learning models
Required Qualifications:
6+ years of relevant experience developing scalable d
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