> Markdown version of [/jobs/ext/1275048-lead-analytics-engineer-enterprise-data-ai](https://www.wearedevelopers.com/jobs/ext/1275048-lead-analytics-engineer-enterprise-data-ai). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Lead Analytics Engineer - Enterprise, Data & AI - **Company:** Zoox - **Location:** Foster City, CA, United States - **Experience:** Expert - **Salary:** $236,000.0 - $284,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Airflow, Data Analysis, Automation of Tests, BigQuery, Data Architecture, Data Structures, Executive Information Systems, Python (Programming Language), Performance Tuning, Query Optimization, Cloud Services, Anaplan, Salesforce.Com, SAP (Applications), SQL Databases, Tableau (Software), Large Language Models, Snowflake, Kubernetes, Low Latency, Data Analytics, SAP S/4HANA, SAP Ariba, Tools for Reporting, Streamlit Framework, Software Version Control, Workday, SAP BRIM (Billing and Revenue Innovation Management), Databricks - **Published:** July 15, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=9d551959b3e02760 ## About the Role * 10+ years in Data Engineering & Analytics, with extensive hands-on experience building a semantic framework using Python, SQL and modern orchestration frameworks (e.g. Airflow, Lakeflow, Argo). With at least 2+ years of hands-on experience deploying AI generated code. * Extensive experience using modern data stacks (e.g. Snowflake/Databricks, Big Query) to build complex, enterprise-grade data models. * Deep understanding of data structures within large-scale enterprise platforms (SAP S/4HANA, Salesforce, Workday, etc.) and the ability to reconcile disparate schemas into clean models. * Exceptional ability to design modular, scalable, and performant data architectures that prioritize ease of use for downstream AI agents and Analytics tools. * A track record of driving technical projects from design to completion, mentoring junior engineers, and fostering a culture of collaboration and data excellence., * Experience using LLMs to automate data reconciliation, anomaly detection or root-cause analysis within analytics pipelines with cloud-native data platforms (e.g., Snowflake, Databricks). * Expert-level Python & SQL skills with a focus on query optimization and performance tuning for massive datasets and reviewing AI generated code. * Proficiency in creating self-service Analytics environments (e.g., Tableau, Streamlit) that provide actionable insights to business stakeholders. ## Description Zoox is seeking a high-agency, hands-on Lead Analytics Engineer to bridge the gap between our complex enterprise data sources and our AI-driven decision-making systems. You will lead the design and implementation of our semantic layer and data modeling strategy, ensuring that data from SAP (S/4HANA, Ariba, BRIM, ME), Workday, Salesforce, and Anaplan is transformed into clean, performant, and "AI-ready" datasets. This is a critical leadership role for a builder who wants to own the data foundation that powers our intelligent agents and business-wide analytical workflows., * Design and maintain a unified semantic model that provides a "single source of truth" for cross-functional stakeholders, AI Agents, Self Serve Analytics and Executive dashboards. * Collaborate with Data & AI Engineers to structure and optimize the data that allows to query enterprise knowledge with high accuracy and low latency. * Establish organizational standards for data modeling, version control, testing, and documentation to ensure high data quality and system maintainability. * Implement automated testing and observability frameworks that proactively identify data anomalies and "self-heal" pipelines, ensuring our data is always reliable for downstream consumption. * Partner with cross-functional business leaders to translate complex operational requirements into high-impact, scalable data solutions. ## Related Videos - [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) - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Destigmatizing the Workplace: Building Real Inclusion](https://www.wearedevelopers.com/videos/1492-destigmatizing-the-workplace-building-real-inclusion) - [The Future of Employee Wellbeing: Benefits, Trust & Performance](https://www.wearedevelopers.com/videos/1808-the-future-of-employee-wellbeing-benefits-trust-performance) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) - [Empowering Retail Through Applied Machine Learning](https://www.wearedevelopers.com/videos/976-empowering-retail-through-applied-machine-learning) ## Related Articles - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [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) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [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)