Senior Data Infrastructure Engineer - Edge-Case & Data Lake

XPENG Jordan; Santa Clara (CA); On-site; USD 175,000 - 296,000; Full time

Benefits offered by this job

Competitive compensation package

Snacks and lunches

Job summary

XPENG is seeking a Data Infrastructure Engineer to analyze massive field datasets and identify corner cases in autonomous driving to enhance safety and comfort. The role involves building scalable data lake and data warehouse infrastructure, managing data quality, and collaborating with ML engineers and annotation teams to apply data-centric AI principles.

You will work with in-house toolchains, contribute to distributed data processing, and support data storage and analytics for cutting-edge

Qualifications

• BS in Computer Science or related field is required.
• 3+ years of industrial experience in data engineering or related field.
• Proficient in English and Mandarin; strong communication skills.
• Experience with data lakes, data warehouses, and ETL/ELT pipelines.
• Familiar with data modeling, schema design, data quality, and orchestration.

Responsibilities

• Identify edge cases in autonomous driving functionality by analyzing large field datasets.
• Resolve edge cases using in-house tools and collaborate with ML Engineers and Annotation Team.
• Monitor efficiency metrics, analyze root causes, and suggest process improvements.
• Build and maintain scalable data lake and data warehouse infrastructure, including ingestion, storage, processing, and analytics pipelines.
• Manage data quality, schemas, metadata, access controls, and system performance for large-scale data.

Skills

English & Mandarin proficiency

Strong communication

Result-driven mindset

Education

BS in Computer Science or related field

Tools

SQL

Python

Data Lakes

Data Warehouses

ETL/ELT Pipelines

Distributed Data Processing

Cloud Storage

Data Modeling

Schema Design

Workflow Orchestration

Job description

XPENG is seeking a Data Infrastructure Engineer to analyze massive field datasets and identify corner cases in autonomous driving to enhance safety and comfort. The role involves building scalable data lake and data warehouse infrastructure, managing data quality, and collaborating with ML engineers and annotation teams to apply data-centric AI principles.

You will work with in-house toolchains, contribute to distributed data processing, and support data storage and analytics for cutting-edge