AI Parts Supply Chain Application Engineer

Lenovo
Lenovo

Software Engineering, Operations, Data Science

Shenzhen, Guangdong, China

Posted on Aug 31, 2026

General Information

Req #
100017557
Career area:
Artificial Intelligence
Country/Region:
China
State:
Guangdong
City:
深圳(Shenzhen)
Date:
Monday, August 31, 2026
Additional Locations:
* China

Why Work at Lenovo

We are Lenovo. We do what we say. We own what we do. We WOW our customers.
Lenovo is a US$83 billion revenue global technology powerhouse, ranked #153 in the Fortune Global 500, and serving millions of customers every day in 180 markets. Focused on a bold vision to deliver Smarter Technology for All, Lenovo has built on its success as the world’s largest PC company with a full-stack portfolio of AI-enabled, AI-ready, and AI-optimized devices (PCs, workstations, smartphones, tablets), infrastructure (server, storage, edge, high performance computing and software defined infrastructure), software, solutions, and services. Lenovo’s continued investment in world-changing innovation is building a more equitable, trustworthy, and smarter future for everyone, everywhere. Lenovo is listed on the Hong Kong stock exchange under Lenovo Group Limited (HKSE: 992) (ADR: LNVGY).
To find out more visit www.lenovo.com and read about the latest news via our StoryHub.

Description and Requirements

Role Summary

We are hiring a Senior Data Engineer to support WW Service Supply Chain operations across Repair, Reverse, and Refurbish. This role focuses on billing data systems, complex SQL procedures, Python ETL, and cross-system data integration. The ideal candidate can own ambiguous legacy logic, turn business rules into reliable data processes, and use AI-assisted coding tools to work efficiently.

Job Responsibilities

  • Maintain and improve billing-related data workflows that support Repair, Reverse, and Refurbish operations.
  • Analyze, optimize, and document complex SQL stored procedures and core business logic.
  • Build and maintain Python ETL pipelines for data ingestion, transformation, and synchronization across systems.
  • Support the evolution of billing logic toward more granular repair-level or RMA-level data structures.
  • Investigate data issues, reconcile cross-system inconsistencies, and improve data quality and traceability.
  • Partner with business, operations, and finance stakeholders to translate process rules into maintainable data solutions.
  • Produce clear technical documentation and structured handover materials for key jobs, procedures, and data sources.
  • Use AI-assisted coding and rapid prototyping practices to accelerate analysis, documentation, and delivery.

Job Requirements:

  • Bachelor's degree or above in Computer Science, Information Systems, Data Engineering, Mathematics, or a related field.
  • 5+ years of experience in data engineering, analytics engineering, or backend data platform development.
  • Strong SQL skills, including complex queries, aggregations, stored procedures, and performance tuning.
  • Solid Python experience for ETL, automation, and data processing.
  • Good understanding of data warehousing and layered data models.
  • Experience supporting business-critical or legacy data systems with complex logic.
  • Ability to communicate clearly with both technical and non-technical stakeholders.
  • Comfortable using AI-assisted coding tools to improve development efficiency and code understanding.

Preferred Qualifications

  • Experience in billing, finance data, supply chain, repair operations, or reverse logistics.
  • Familiarity with Service Supply Chain workflows, especially Repair, Reverse, and Refurbish.
  • Experience refactoring legacy data processes into more scalable and traceable designs.
  • Exposure to reinforcement learning, optimization, or allocation-rule modeling is a plus, but not required.
  • AI agent deployment experience.

What We Value

  • Strong ownership of high-impact data and business logic.
  • Practical problem-solving in complex and evolving system environments.
  • Clear documentation habits and structured handover capability.
  • A fast, iterative working style with effective use of AI-assisted coding.

Additional Locations:
* China
* China