Job Description

As a Data Engineer II on the Product Insights Data Team , you'll work closely with engineers, analysts, and data scientists to develop scalable and reliable data systems supporting multiple game titles. Your efforts will directly enhance the player experience through high-quality data insights. In this role, you will design and maintain performant ETL pipelines, build reusable and efficient data models, and ensure robust governance, security, and compliance practices. Reporting to the Manager of the Product Insights Data Team, you'll contribute to game-specific data solutions and help drive data-informed decision-making across our game development lifecycle.

Key Responsibilities

• Implement and uphold best practices in data engineering, including scalable architecture, clean and maintainable code, high service quality, comprehensive monitoring, and clear documentation.
• Partner with engineers, analysts, and data scientists to develop and sustain scalable backend data infrastructure.
• Design reusable data marts and telemetry frameworks applicable across various game titles.
• Safeguard player data through rigorous privacy and security standards in all data solutions.
• Build scalable systems that meet the evolving data requirements of Riot’s game development efforts.

Required Qualifications

• 5+ years of experience in data or software engineering, including internships and academic/postgraduate experience.
• Demonstrated success in designing and delivering end-to-end, production-grade data systems.
• Strong proficiency in Python , PySpark , SQL , and data orchestration tools such as Airflow and DBT .
• Hands-on experience with cloud platforms such as AWS or GCP , and advanced use of Databricks .
• Expertise in data modeling within large, complex ecosystems.
• Experience mentoring junior team members and contributing to team development.
• Bachelor's degree in Computer Science or a related field, or equivalent professional experience.

Preferred Qualifications

• Proficiency in additional programming languages such as Java or Scala .
• Strong working knowledge of SQL and relational database systems.
• Experience with business analytics or other data-driven disciplines.
• Practical experience with data processing tools such as Spark and BigQuery .
• Experience with orchestration tools like Airflow for workflow automation.
• Familiarity with AWS data services and tools for querying and managing data.
• Collaborated with software engineers to design and implement robust testing strategies for data pipelines.

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