Principal Analytics Engineer, Riot Games

• 8+ years of professional experience, including 4+ in a technical analytics role (data, business intelligence, analyst)
• 4+ years of data visualization experience with Tableau, ThoughtSpot, Looker, PowerBI, Mode or similar tools
• 4+ years of experience with data modeling for reporting or business use cases
• Expertise using SQL in large-scale data warehousing environments
• Passion for producing high impact data products at scale
• ETL experience with Spark and/or Databricks
• For this role, you'll find success through craft expertise, a collaborative spirit, and decision-making that prioritizes your fellow Rioters, who are the customers of your work
• Being a dedicated fan of games is not necessary for this position!

Desirable

• As a Principal Analytics Engineer on the Central Product Insights team, you’ll be responsible for creating, owning and maintaining context-heavy, business-centric data models that help empower teams to achieve Riot’s strategic goals
• The Central Product Insights (CPI) team at Riot is focused on delivering portfolio level game insights, both to help individual game teams optimize their products with consideration for the greater Riot ecosystem, and to aid business leaders in making data-informed strategic decisions
• You will be embedded within the Central Product Insights team to build and maintain critical data pipelines used to assess product health and identify new strategic opportunities
• You will develop high-leverage dashboards, bespoke product analyses, and curate data sources to answer key business questions across Riot’s entire portfolio
• You will report directly to the Analytics Lead within the Data Organization, and be deployed on the CPI team as an embedded specialist
• Analytics Engineers create the fabric that connects Data Science, Data Engineering, Data Insights and Product Managers
• They have a deep understanding of how Riot’s goals translate into measurable business outcomes that can be tracked, validated and informed by data
• Their passion for problem solving lets them translate business questions into evergreen data tools that enable self-service to all Rioters
• In doing so, they build foundational data sets that are the basis for centralized reporting, analysis, experimentation and machine learning applications
• Understand and anticipate data needs by owning key stakeholder relationships across multiple product teams. Serve as liaison between data, product and insights teams
• Architect, implement and own central data models that transform data from disparate sources into fully integrated, high-context datasets
• Engineer efficient and scalable ETL pipelines in partnership with data engineering
• Design, test and socialize new metrics that connect Riot data to desired business outcomes
• Publish high-impact dashboards to enable self-service of data questions
• Champion data governance best practices through robust documentation and lineage maps to curated sources of truth
• Partner with Data Science to produce models consumable by Machine Learning applications