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OpenAI is seeking an Analytics Engineer to join the Data team within the Go-to-Market organization. This is a full-stack data role spanning data modeling, metric definition, visualization, analysis, and self-service tooling. You will build trusted, scalable data sources and products that deliver reliable, actionable insights to the business.
You will partner closely with GTM teams to identify high-impact questions and translate business needs into data models, metrics, analyses, and scalable technical solutions. Key responsibilities include defining, sourcing, validating, and operationalizing metrics that guide business decisions; leading cross-functional data projects across established and emerging business areas; building scalable data models and pipelines that integrate data from multiple sources; and creating dashboards, reports, and analytical tools that enable stakeholders to answer questions independently.
You will own the complete lifecycle of metrics, analytical models, and data products from exploration through production and maintenance. The role requires exercising strong judgment when prioritizing competing requests, balancing immediate business needs with long-term ecosystem improvements. You will turn complex findings into clear, persuasive narratives through presentations, memos, dashboards, and other formats suited to your audience.
Ideal candidates bring 10+ years of experience in data roles within fast-moving, results-oriented organizations. You should be highly autonomous and resourceful, capable of independently structuring and owning ambiguous, high-impact business problems. Deep SQL expertise, experience with large datasets and ETL workflows, and proficiency in Python are essential. Experience with BI tools (Tableau, Looker) and custom visualization frameworks (React, Streamlit, Plotly Dash) is expected. You should have delivered significant business impact, ideally within Sales, Finance, Support, or another GTM function, and bring exceptional attention to detail and commitment to accuracy.
