Analytics Engineer 5 - Cloud Games Infrastructure Data Products

Partner closely with our engineering teams to develop deep expertise in how the cloud gaming infrastructure works, across both quality of experience and capacity and utilization, and understand how data, analytics, experimentation, and algorithms can drive improvements to its performance and how we invest in it. Own the analytic data layer and the data products (pipelines, tables, dashboards, AI agents, tooling, and self-service assets) that turn our QoE framework and our capacity and utilization characterization into reliable insights for partners. Work across the entire data stack, including telemetry extension and logging, data modeling, metrics development, visualization, and insights generation, to drive alignment of resources against the most important problems in this space. Build toward self-service access rather than ad hoc delivery, and ensure what the team publishes is trustworthy, well-documented, and maintainable over time. Independently identify and drive the highest-leverage investments across the cloud games infrastructure data domain. Passion for solving real-world problems through analytics, tooling, and visualization, and an eye for independently identifying new, impactful analytic opportunities. Expertise in SQL (Trino, Spark SQL), programming (e.g., Python), ETL, and data warehousing concepts at scale. Previous dbt experience as a bonus. An appetite for learning and adopting AI capabilities as a means to supercharge your workflow, paired with the judgment to know when their output is trustworthy and explainable enough to act on. Curiosity to pursue deep expertise in data science and engineering with a detailed understanding of distributed systems engineering and networking. Experience developing pipelines of moderate complexity on massive telemetry data sets, with the ability to effectively partner with data engineering teams, building more scalable solutions for the most important use cases. Strong judgment about where to invest, the discipline to keep sight of the bigger picture, and a bias toward durable, scalable capability over one-off outputs. Experience building strong partnerships and communicating technical and analytical concepts clearly and concisely among audiences at many different levels. Comfort with ambiguity and the ability to thrive with minimal oversight and process.