Associate Data Engineer

Lenovo

Data Science

Kuala Lumpur, Malaysia

Posted on May 12, 2026

General Information

Req #

WD00097721

Career area:

Data Management and Analytics

Country/Region:

Malaysia

State:

Wilayah Persekutuan Kuala Lumpur

City:

Kuala Lumpur

Date:

Tuesday, April 28, 2026

Working time:

Full-time

Additional Locations:

* Malaysia

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$69 billion revenue global technology powerhouse, ranked #196 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).

This transformation together with Lenovo’s world-changing innovation is building a more inclusive, trustworthy, and smarter future for everyone, everywhere. To find out more visit www.lenovo.com, and read about the latest news via our StoryHub.

Description and Requirements

Our tech team is seeking a passionate Data Engineer to design, build and scale our enterprise-level data platform, while enabling seamless integration with our growing AI product ecosystem. You will own end-to-end development of data pipelines, ETL jobs, leverage AI/ML tools to realize business use cases.

Key Requirements

Working experience in data engineering, with proven hands-on experience in designing, developing and maintaining large-scale distributed Data Platforms
Proficient in SQL, Python, and common big data tools (Spark/Hive), solid foundation in data modeling and ETL architecture
Better understanding of AI/ML principles, familiarity with model data preparation, feature engineering or LLM data processing workflows is preferred
Strong analytical thinking, good communication skills, and ability to work independently in agile teams