Principal Data Engineer, Personalization - Central Product Insights

About the Role

As a Principal Data Engineer supporting Riot’s Central Product Insights, you will design, build, and maintain scalable data pipelines and models that power critical data products, including centralized player data models and publishing activity data systems. These systems support understanding of player onboarding funnels, engagement patterns, support efficiency, and content effectiveness. You will collaborate with product managers, analysts, and engineers to ensure data infrastructure is reliable, performant, and directly tied to delivering better player experiences.

Responsibilities

• Design, build, and optimize scalable ETL pipelines for structured and semi-structured data supporting Insights use cases, growth metrics, and other publishing/marketing-focused data sets.
• Design and implement data models using industry best practices that capture a complete ecosystem view of in- and out-of-game experiences, ensuring accuracy, scalability, and long-term usability.
• Architect and implement robust, maintainable, and high-performance data solutions.
• Automate workflows to reduce manual intervention and enhance data processing efficiency, including automation for content, growth, and pubsports coverage.
• Mentor data engineers across all levels, setting best practices and fostering technical growth.
• Optimize query performance and resolve pipeline bottlenecks to improve data accessibility.
• Evaluate and adopt new tools, frameworks, and methodologies to advance data engineering capabilities.
• Support cost optimization by ensuring scalable and efficient data solutions.
• Ensure data quality, governance, and compliance with regulatory standards (e.g., GDPR, CCPA).
• Contribute to Riot’s Data Engineering discipline shaping infrastructure, craft standards, tooling, and organizational best practices.

Qualifications

Required

• Bachelor's or Master’s degree in Computer Science, Information Systems, Engineering, or a related field.
• 8+ years of experience in tech-focused Publishing or Marketing fields.
• 8+ years of experience in data engineering or a related field.
• Strong expertise in big-data technologies, including Python, Go, Apache Spark, Scala, SQL, and tools like Apache Airflow and dbt.
• Proficiency in cloud infrastructure (AWS or GCP) and Databricks.
• Expertise in designing efficient and scalable data models with large data sets across multiple teams and in collaboration with insights or data stakeholders.
• Demonstrated ability to work cross-functionally with engineering, analytics, and product teams.
• Proven experience mentoring and guiding other engineers.

Desired

• Experience in gaming, large consumer platforms, or systems leading data modernization or transformation initiatives in a complex environment.
• Track record improving data maturity (e.g., SLI/SLO governance, reliability standards) and experience designing semantic layers or standardized business metric frameworks.
• Background supporting advanced analytics use cases in high-velocity product environments.
• Demonstrated ability to influence standards across teams in a matrixed organization.