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Kerja Sepenuh Masa, Data Quality Expert di Lenovo Federal Territory - Maukerja

KL City, Federal Territory

Kongsi
Simpan

Lokasi Kerja

  • Kuala Lumpur Federal Territory Malaysia

Penerangan Kerja

Tanggungjawab

General Information

Req #
WD00105123
Career area:
Data Management and Analytics
Country/Region:
Malaysia
State:
Wilayah Persekutuan Kuala Lumpur
City:
Kuala Lumpur
Date:
Wednesday, October 21, 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$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).


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 *************, and read about the latest news via our StoryHub.

Description and Requirements

Key Responsibilities

Data Quality Engineering

  • Design, develop, and maintain scalable data quality rules, scorecards, and monitoring mechanisms across enterprise data assets.
  • Develop automated data validation and reconciliation processes throughout data ingestion, transformation, and consumption layers.
  • Design proper solution to integrate data quality checks into data pipelines and CI/CD deployment processes to enable automated quality enforcement.

Monitoring & Operational Excellence

  • Monitor enterprise data quality health and proactively identify quality issues, anomalies, and risks.
  • Investigate root causes of data quality incidents and collaborate with engineering and business teams to drive remediation.
  • Establish alerts, dashboards, KPI tracking, and reporting mechanisms for enterprise data quality performance.
  • Support operational governance processes for issue management, escalation, tracking, and resolution.

Platform & Automation Enablement

  • Partner with data platform teams to embed data quality capabilities into enterprise data platforms.
  • Contribute to self-service data quality capabilities, reusable rule libraries, and standardized quality frameworks.
  • Leverage AI and automation technologies to improve rule generation, anomaly detection, root cause analysis, and monitoring efficiency.
  • Support continuous enhancement of Data Quality Services (DQS), scorecard engines, and related platforms.

Governance & Stakeholder Collaboration

  • Collaborate with Data Governance, Data Stewards, Data Owners, and business teams to define quality requirements and acceptance criteria.
  • Translate business requirements into executable technical data quality controls.
  • Support enterprise standards, policies, and governance processes related to data quality.
  • Drive adoption of data quality best practices across business and IT organizations.

Qualifications

Education

  • Bachelor's degree or above in Computer Science, Information Systems, Data Engineering, Statistics, or a related discipline.

Experience

  • 8+ years of experience in Data Quality, Data Engineering, Data Governance, Analytics Engineering, or related fields.
  • Hands-on experience implementing enterprise data quality solutions and monitoring frameworks.
  • Experience working with large-scale data platforms, data warehouses, data lakes, or lakehouse architectures.

Technical Skills

  • Strong SQL skills with experience in data profiling, validation, reconciliation, and troubleshooting.
  • Proficiency in Python, Spark, PySpark, or similar data engineering technologies.
  • Experience with Databricks, Azure Data Factory, Azure Data Lake, or comparable cloud-based data platforms.
  • Familiarity with data quality tools, metadata management, catalog solutions, etc.
  • Knowledge of data modeling, ETL/ELT processes, and data pipeline orchestration.

Preferred Qualifications

  • Understanding of Data Governance, Metadata Management, Master Data Management (MDM), and Data Lineage concepts.
  • Experience implementing rule-based and AI-driven data quality capabilities.
  • Knowledge of enterprise data architecture and analytics ecosystems.
  • Experience supporting global or cross-functional data programs.
  • Relevant certifications in Azure, Databricks, Data Management, or Data Governance are a plus.
Additional Locations:
  • Malaysia
  • Malaysia

Peringatan Penting

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