Director, Data Engineering – Player Lifecycle & Personalization

Los Angeles · 5+ years experience · Remote · Posted Oct 12, 2026

At a glance

As a Director of Data Engineering within the PubSports organization, you will define and lead the data strategy supporting Player Lifecycle & Personalization across Riot.
This role is responsible for building the data products, data foundations, and organizational capabilities that enable player understanding, segmentation, personalization, experimentation, analytics, and AI-driven experiences.
In addition to owning Player Lifecycle & Personalization, you will lead the modernization and evolution of PubSports' data ecosystem, driving adoption of Riot's data platform standards while establishing a long-term strategy for player intelligence and engagement data.

Define and execute the data strategy for Player Lifecycle & Personalization across Riot.
Establish trusted player data products, data models, and intelligence capabilities that support engagement, retention, personalization, experimentation, and AI-driven experiences.
Partner with Product, Insights, Data Science, and AI leaders to translate business needs into scalable data capabilities and platforms.
Lead modernization of PubSports' data ecosystem and improve data quality, governance, observability, and operational accountability.
Drive standardization of player data, business metrics, and semantic definitions across teams.
Build and grow a high-performing organization of managers, senior engineers, and technical leaders.
Define long-term investment priorities and roadmap for Player Lifecycle & Personalization data capabilities.
Communicate strategy, priorities, risks, and outcomes to senior leadership and stakeholders.

Bachelor’s degree in Computer Science or a related field, or equivalent experience.
12+ years of experience in data engineering, data platforms, analytics engineering, or related disciplines.
5+ years of people leadership experience, including experience leading managers and senior technical leaders.
Experience leading data engineering, machine learning engineering, data platform, analytics engineering, or customer intelligence organizations.
Experience building data products and data capabilities that support lifecycle management, personalization, customer intelligence, loyalty, CRM, or similar domains.
Strong leadership experience building teams, developing managers, and delivering through others.
Experience defining strategy and operating effectively in ambiguous environments.
Deep understanding of modern data platforms, data products, governance, and data quality practices including Agentic DE AI platforms
Proven ability to partner across Product, Analytics, Data Science, Engineering, and executive leadership teams.

Master’s degree in Computer Science or a related field, or equivalent experience.
Experience with large-scale data platforms in gaming or adjacent consumer products.
Familiarity with large-scale experimentation platforms and cross-surface measurement.
Experience with autonomous AI coding platforms, modern data platforms, including transformation frameworks and governance or metadata tooling (e.g., Devin, Databricks, Atlan).
Experience leading platform-focused engineering organizations.
Experience leading and scaling distributed or remote teams.
Experience supporting machine learning, experimentation, and AI-driven products.
Experience leading data modernization and organizational data maturity initiatives.