Staff Data Engineer, Sales Analytics Infrastructure, AI & Agentic Solutions
Tesla
Fremont, CA, US
Onsite
2026-07-01
Announced salary
$180,000 - $270,000
Low
$102K
Median
$117K
High
$201K
Market in Fremont · offers-geo 2025
Estimated net pay
$10,157 - $14,624
/month · 32% withheld
after tax & contributions · Single, no dependents
Job description
**What to Expect**
The Business Analytics team’s mission is to enable a data\-driven business and generate knowledge from our data, directly supporting business leaders from our retail locations to headquarters and up to our leadership team.
This role is the engineering and automation backbone of that mission. You will own and scale the data infrastructure behind our source\-of\-truth datasets, KPI pipelines, and dashboards, and build the agentic tooling that automates how our team works. A significant focus is market data engineering, partnering directly with external vendors to design and integrate API\-based data feeds (e.g., registrations, market share) for our planning and Customer Insights teams. This is a senior individual\-contributor role: you will set technical direction and act as the go\-to expert for our data platform and agentic stack.
**What You'll Do**
* Own, maintain, and scale our core data infrastructure: Airflow orchestration, ClickHouse database, and the jobs and pipelines that feed our internal datasets and with strong observability and data\-quality checks
* Lead market\-data acquisition: partner with external vendors to scope and build API\-based integrations and automated feeds, handling authentication, refresh scheduling, schema\-change resilience, and reconciliation
* Normalize heterogeneous vendor and internal data (e.g., Maxim endpoints) into clean, well\-modeled, self\-serve datasets that democratize market data across the organization
* Partner with Analysts in our team to productionize ad\-hoc analyses into maintainable pipelines and provide self\-serve tooling and engineering best practices
* Support customer insights / survey \& CSAT data needs as a secondary workload, including NLP/AI on feedback
* Build agentic workflows to automate recurring team tasks, maintain the team’s knowledge base, and develop domain\-specific agents that integrate with our data endpoints
* Manage infrastructure operations: CI/CD, credentials/secret
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