Data Quality Expert

Lenovo; Kuala Lumpur; Vor Ort; MYR 180.000 - 260.000; Vollzeit

Zusammenfassung

Lenovo is seeking a senior Data Quality Engineer to design, implement, and monitor scalable quality rules across enterprise data assets. You will collaborate with data platform teams to embed quality checks into pipelines and CI/CD workflows, enabling automated governance and remediation.

Strong SQL, Python, Spark, and cloud data tools are essential for success. With 8+ years in Data Quality, Data Governance, or Analytics Engineering, you will partner with business teams to translate

Qualifikationen

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

Aufgaben

• 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.

Kenntnisse

SQL

Python

Spark/PySpark

Data profiling

ETL/ELT

Data modeling

Ausbildung

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

Tools

Databricks

Azure Data Factory

Azure Data Lake

Data quality tools

Metadata management

Catalog solutions

Jobbeschreibung

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 www.lenovo.com , 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.

If you require an accommodation to complete this application, please contact [e-mail]