Lead Analytics Engineer – Enterprise, Data & AI
Zoox is hiring a Lead Analytics Engineer – Enterprise, Data & AI in Foster City, United States. It pays $230k-$315k a year and Level rates it ; you can apply on Zoox.
Level's read on this job
- Works on AI ●●●○ is how Level rates this role: the daily work is on AI products, without building the model.
- Tools and skills the posting cites include Databricks and AI agents.
- Level classifies it as a lead role.
- Level lists 228 other open roles at Zoox.
AI in this role
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 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.
Bonus Qualifications:
- 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.
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AccommodationsIf you need an accommodation to participate in the application or interview process please reach out to accommodations@zoox.com or your assigned recruiter.
A Final Note:You do not need to match every listed expectation to apply for this position. Here at Zoox, we know that diverse perspectives foster the innovation we need to be successful, and we are committed to building a team that encompasses a variety of backgrounds, experiences, and skills.
How we rate this
Lead Analytics Engineer – Enterprise, Data & AI at Zoox rates 63 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- How do you decide when an AI agent can act on its own versus asking for approval first?
- Walk me through how you've used Databricks in your day-to-day work.
- Describe a typical day in a role like this one: which parts run through AI directly?
- If you removed AI from this role, what would be left, and how do you decide what still needs a human?
Adapt your resume
- List these exact terms on your resume: AI agents and Databricks. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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