Data Engineer

About the Role As a Data Engineer in Riot Data Foundations on the Data Experiences and Automation team, you will have the chance to affect how Riot collects and uses data to improve the experience for players and Rioters. You'll work closely with our technical lead to expand data consumption and reporting capabilities and build solutions to improve the development lifecycle for data engineers and insight analysts throughout the organization. You'll be helping as Riot enables advancements and fast iteration in Machine Learning and GenAI pipelines. You will bring your experience working with globally distributed systems and work with our team of software engineers to help build efficient solutions. You will report into the Engineering Manager of the team. Responsibilities Design, build, and optimize scalable pipelines for data supporting insight into the Data Foundation ecosystem. Design and implement data models using industry best practices that capture a complete ecosystem view of internal customer 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. 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 Bachelor's or Master’s degree in Computer Science, Information Systems, Engineering, or a related field. 5+ years experience in data engineering or a related field. Strong Expertise in big-data technologies, including Python, GoLang, Spark, Scala, SQL, and tools like Airflow and dbt. Proficiency in cloud infrastructure (AWS) 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. Required Skills Strong Expertise in big-data technologies, including Python, GoLang, Spark, Scala, SQL, and tools like Airflow and dbt. Preferred Skills Experience with ML Operations and GenAI pipelines and infrastructure.