Senior Data Infrastructure Engineer — Edge Case & Data Lake

XPENG; Santa Clara (CA); On-site; USD 174,720 - 295,680; Full time

Benefits offered by this job

Snacks & lunches

Fun activities

Competitive compensation package

Job summary

XPENG, a leading smart mobility company, is seeking a Data Infrastructure Engineer to analyze massive autonomous driving datasets and identify corner cases affecting safety or comfort. You will collaborate with ML engineers and annotation teams to apply data-centric AI principles and build scalable data pipelines.

You will design and maintain data lakes and data warehouses, ensure data quality, schemas, and robust access controls while optimizing performance across large-scale data

Qualifications

• BS in Computer Science or related field.
• 3+ years of industrial data engineering experience.
• Proficient in English and Mandarin.
• Experience with data lakes and data warehouses.
• Familiar with data modeling, schema design, data quality management, and workflow orchestration.

Responsibilities

• Identify edge cases in autonomous driving functionality by analyzing massive field data.
• Resolve edge cases with in-house toolchains in collaboration with ML engineers & Annotation Team.
• Monitor key efficiency metrics in edge case resolving process and identify 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.

Skills

Data analysis

SQL

Python

Bilingual English/Mandarin

Education

BS in Computer Science or related field

Tools

SQL databases

ETL/ELT pipelines

Cloud storage systems

Job description

XPENG, a leading smart mobility company, is seeking a Data Infrastructure Engineer to analyze massive autonomous driving datasets and identify corner cases affecting safety or comfort. You will collaborate with ML engineers and annotation teams to apply data-centric AI principles and build scalable data pipelines.

You will design and maintain data lakes and data warehouses, ensure data quality, schemas, and robust access controls while optimizing performance across large-scale data