Senior Data Infrastructure Engineer at XPENG
Santa Clara, CA
$174,720–$295,680from the description
Jul 26, 2026
Santa Clara, CA
Jul 28, 2026
What this job asks for AI summary
This role sits at the intersection of autonomous driving data operations and data infrastructure engineering. The engineer will analyze large-scale field datasets to identify edge cases that could affect vehicle safety or comfort, then work with ML and annotation teams to resolve them. They will also build and maintain data lake and warehouse pipelines, manage data quality and schemas, and keep the broader data infrastructure running reliably at scale.
Mid level · 3+ years · Full-time
Posted 2 times — it's one opening, so apply once.
We read this from the posting text with AI. Skim the description below before ruling yourself out.
How this req sits in the market our data
Most people in this occupation already list these. Still required — just not what gets you shortlisted.
What the occupation pays Median $142,568 (middle half $111,775–$173,013). This posting is about at that midpoint.
Estimated from BLS employment for this occupation and area, per-skill prevalence across our listing corpus, and published wage benchmarks — as of Jul 28, 2026. It is a model, not a headcount.
Why we read it this way (5)
The role blends two distinct functions — edge-case analysis on autonomous driving datasets (closer to data/operations analysis) and building/maintaining data lake and warehouse infrastructure (closer to data architecture/engineering). The SOC code reflects the infrastructure-building side as the primary engineering deliverable, but the alt code reflects the analytical edge-case work.
Bilingual proficiency in English and Mandarin is listed as a hard requirement but is not a technology skill and so is not captured in the skills list.
The degree requirement states 'BS in Computer Science or related fields (or relevant experience)', which allows equivalent experience in lieu of a degree — treated as no hard degree gate.
Data modeling, schema design, data quality management, and workflow orchestration appear under a 'Familiarity with' qualifier in the Requirements section, indicating familiarity rather than deep expertise — marked as preferred accordingly.
Ignored 3 non-technology phrase(s) as skills (responsibilities/concepts, not named tools): schema design, data quality management, workflow orchestration.
Read the full posting
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