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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Analytics Engineer - **Company:** OpenAI Inc. - **Location:** San Francisco, CA, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Clean Code Principles, Adaptable Database Systems, Artificial Intelligence, Business Analytics Applications, Data Analysis, Big Data, Databases, Data Files, Extract Transform Load (ETL), Data Visualization, Programming Tools, Python (Programming Language), Operational Databases, Systems Development Life Cycle, Standard Sql, Software Engineering, SQL Databases, Tableau (Software), Scripting, ReactJS, Data Strategy, Plotly, Data Management, Streamlit Framework, Looker Analytics, Programming Languages - **Published:** August 14, 2026 - **Apply:** https://www.careerbuilder.com/job-details/analytics-engineer-gtm-san-francisco-ca--e255948b-cddf-4418-8508-2b7a0c665221 ## About the Role * Have 10+ years of experience in a relevant data role within fast-moving, results-oriented organizations. * Can independently structure and own ambiguous, high-impact business problems from initial framing through recommendation and execution. * Are highly autonomous, resourceful, and creative when navigating technical, operational, and stakeholder constraints. * Exercise strong judgment when deciding what to prioritize, how deeply to invest, and when a quick answer should become a durable data product. * Have deep SQL expertise and extensive experience working with large datasets and designing ETL workflows. * Understand effective software and analytics engineering practices and can use AI tools to move faster without creating brittle systems, unclear code, or unnecessary complexity. * Are proficient in a quantitative programming language, preferably Python. * Have experience with BI tools such as Tableau or Looker and know how to enable effective self-service analytics. * Have worked with custom visualization frameworks such as React, Streamlit, or Plotly Dash. * Can turn complex analysis into persuasive stories using memos, presentations, dashboards, and other formats. * Bring exceptional attention to detail and a strong commitment to accuracy. * Have delivered significant business impact, ideally within Sales, Finance, Support, or another GTM function., Affirmative Action, Analysis Skills, Artificial Intelligence (AI), Business Intelligence Software, Cross-Functional, Data Analysis, Data Management, Data Modeling, Data Sets, Data Visualization, Database Extract Transform and Load (ETL), Detail Oriented, Documentation Models, Ecosystems, Equal Employment Opportunity (EEO), Establish Priorities, Finance, Genetics, Looker, Machine Tool, Metrics, Persuasion Skills, Process Improvement, Productivity Management, Programming Languages, Programming Tools, Prototyping, Python Programming/Scripting Language, React.js, Reporting Dashboards, SQL (Structured Query Language), Sales, Scalable System Development, Software Engineering, Strategic Analysis, Strategic Planning, Tableau ## Description As a member of the Data team within the Go-to-Market organization, you will help build a data-driven culture, improve decision-making, and advance strategic initiatives through analytics. 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 give the business reliable, actionable insights. The work calls for judgment: you will choose the tool, approach, and level of investment that best fit each problem, from a focused analysis to a durable production data product. As a core partner to the GTM organization, you will address both foundational and ad hoc analytics needs. You will turn complex data into clear narratives that help technical and non-technical audiences understand what is happening, why it matters, and what they should do next. In this role, you will: * Partner closely with GTM teams to proactively identify high-impact questions and translate business needs into data models, metrics, analyses, and scalable technical solutions. * Define, source, validate, and operationalize the metrics that guide the business, helping teams incorporate them into planning and day-to-day decisions. * Lead cross-functional data projects across established and emerging business areas, including setting the data strategy for greenfield domains. * Build scalable data models and pipelines that integrate and transform data from multiple sources into trusted, accessible datasets. * Create dashboards, reports, analytical tools, and other data products that enable stakeholders to answer questions independently. * Own the lifecycle of metrics, analytical models, and data products from initial exploration and prototyping through production and ongoing maintenance. * Choose the most effective approach for each problem-whether an analysis, metric, data model, visualization, or self-service product-based on the audience, urgency, complexity, and expected value. * Exercise strong judgment when prioritizing competing requests, balancing immediate business needs with investments that improve the long-term quality and scalability of the data ecosystem. * Use AI-assisted development tools to increase productivity while maintaining clear, tested, and maintainable code, data models, and documentation. * Turn complex findings into clear, persuasive narratives through presentations, written memos, dashboards, and other formats suited to the audience. ## Related Videos - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Watch Tests Go Brrrr! : Getting Started with Cypress in ReactJS](https://www.wearedevelopers.com/videos/282-watch-tests-go-brrrr-getting-started-with-cypress-in-reactjs) - [Python Data Visualization @ Deepnote (w/ PyViz overview)](https://www.wearedevelopers.com/videos/113-python-data-visualization-deepnote-w-pyviz-overview) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data) - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production)