Riot Games is looking to solve the complex challenge of turning petabytes of data into meaningful insights to elevate the player experience at massive scale, specifically in the areas of Publishing and eSports.
Requirements
- Strong Expertise in big-data technologies, including Python, GoLang, Spark, Scala, SQL, and tools like 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.
Responsibilities
- Design, build, and optimize scalable ETL pipelines for structured and semi-structured data supporting Insights use cases, growth metrics, pubsports, and other out-of-game data sets.
- Design and implement data models using industry best practices that capture a complete ecosystem view of in- and out-of-game experiences, while 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 areas of coverage.
- Optimize query performance and resolve pipeline bottlenecks to improve data accessibility.
- Evaluate and adopt new tools, frameworks, and methodologies to advance data engineering capabilities.
- Ensure data quality, governance, and compliance with regulatory standards (e.g., GDPR, CCPA).
Other
- Bachelor's or Master’s degree in Computer Science, Information Systems, Engineering, or a related field.
- 8+ years experience in data engineering or a related field.
- Demonstrated ability to work cross-functionally with engineering, analytics, and product teams.
- Proven experience mentoring and guiding other engineers.
- Ability to work in a collaborative environment with a focus on player empathy and delight
