$230K – $315K/yr
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. In this role, you will: 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. Qualifications: 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 platf
