Senior Data Infrastructure Engineer

XPENG

$174K — $295K *
Manufacturing & Automotive
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • BS in Computer Science or related field (or equivalent experience)
  • 3+ years of industrial experience in the data infrastructure or autonomous driving field
  • Proficient in English and Mandarin, both written and spoken
  • Passionate about autonomous driving technology
  • Familiar with SQL and some Python experience
  • Experience with data lakes, data warehouses, ETL/ELT pipelines, and cloud storage systems
  • Familiarity with data modeling, schema design, and data quality management

Responsibilities

  • Identify edge cases in autonomous driving functionality through analysis of large field datasets
  • Resolve edge cases creatively using in-house toolchains while collaborating with Machine Learning Engineers and the Annotation Team
  • Monitor efficiency metrics during edge case resolution, analyze root causes of changes, and propose process improvements
  • Build and maintain scalable data lake and warehouse infrastructure for data ingestion, storage, and processing
  • Manage data quality, access controls, and system performance for autonomous driving data systems

Benefits

  • A fun, supportive, and engaging work environment
  • Chance to significantly impact the advancement of autonomous driving technology
  • Opportunity to work with cutting-edge technologies alongside top industry talent
  • Competitive compensation package
  • Access to snacks, lunches, and fun activities
Full Job Description
We are looking for a Data Infrastructure Engineer with engineering background and development skills. As a Data Infrastructure Engineer, your role is to identify corner cases in autonomous driving functionality that may affect safety or comfort by analyzing massive dataset collected from the field; resolve corner cases with creative methods by leveraging in-house toolchains and work closely with Machine Learning Engineers and Annotation Team to apply principals of data-centric AI to resolve real-world problems. Responsibilities • Identify edge cases in autonomous driving functionality that may affect safety or comfort by analyzing massive dataset collected from the field. • Resolve edge cases with creative methods by leveraging in-house toolchains and working closely with Machine Learning Engineers & Annotation Team. • Monitor key efficiency metrics in edge case resolving process, analyze root causes of changes and provide constructive ways to improve the process • Build and maintain scalable data lake and data warehouse infrastructure, including data ingestion, storage, processing, and analytics pipelines. • Manage data quality, schemas, metadata, access controls, and system performance to ensure reliable and efficient use of large-scale autonomous driving data. Requirements: • BS in Computer Science, or related fields (or relevant experience). • 3 + years industrial experience in the related field. • Proficient in both written and spoken English and Mandarin. • Passionate about autonomous driving technology. • Familiar with SQL and some prior experience with Python. • Experience with data lakes, data warehouses, ETL/ELT pipelines, distributed data processing, or cloud-based storage systems. • Familiarity with data modeling, schema design, data quality management, and workflow orchestration. • Strong communication skills. • Result-driven & can-do attitude. What do we provide: • A fun, supportive and engaging environment. • Opportunity to make significant impact on transportation revolution by the means of advancing autonomous driving. • Opportunity to work on cutting edge technologies with the top talent in the field. • Competitive compensation package. • Snacks, lunches and fun activities. The base salary range for this full-time position is $174,720 - $295,680, in addition to bonus, equity and benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.

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