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XP Power

Engineering Data Analyst

Posted Yesterday
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In-Office
Singapore, SGP
Mid level
In-Office
Singapore, SGP
Mid level
The Engineering Data Analyst manages engineering data integrity within PLM/ERP systems, develops ETL pipelines, conducts data analysis, and builds dashboards to support decision-making and supply chain resilience.
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Company Description

We are committed to our culture that values Customer Focus, Flexibility, Knowledge, Speed and Integrity. Joining our team means you will work in a high performing global company where employees collaborate and strive for excellence. 

Job Description

Position Summary

Acts as a subject-matter expert of engineering data (products, BOMs, materials, Documents, suppliers, etc.)  – Own the end-to-end integrity of engineering data within our PLM/ERP systems;  Bridge hardware engineering, procurement, quality, and IT by establishing frameworks for engineering data gathering, cleansing, and integrity assurance;  Leverage data analytics to manage material and product lifecycles, mitigate supply chain risks, and enable data-driven decision-making; Enable automation, reduce cycle times, and ensure supply chain resilience through trusted master data.

Duties & Responsibilities

  • Develop ETL pipelines, scripts (Python/SQL) and APIs to integrate PLM/ERP systems, supplier portals, market intelligence tools and parametric databases.
  • Analyse material characteristics and parametrics (electrical, mechanical, thermal), supplier details, lifecycle status, cost, lead‑time, quality and compliance data to identify potential data integrity issues.
  • Lead data cleansing initiatives, implement validation rules, and automate data quality checks to ensure material data quality.
  • Analyse product BOMs, utilize material demand and supply data to predict production risk due to material obsolescence and market shortage.
  • Build self‑service dashboards (Power BI/Tableau) for lifecycle/shortage risk, cost variance, supplier performance, and component health.
  • Partner with Design, Procurement, Quality, and Manufacturing to drive cost reduction, lead‑time mitigation, and supplier quality improvements.
  • Partner with IT and engineering teams to optimize system configurations, workflows, and data integration points to ensure material data flows from component engineering to design to manufacturing
  • Maintain documentation, standards, and training for component data and best analytics practices.

Qualifications

  • BEng/BSc in Electrical/Electronic Engineering, Materials, or related.
  • 3+ years of experience in Component Engineering, Material Master Data Management, Supply Chain Analytics, or Data Analytics for hardware.
  • Proficiency in MS Power BI, Power Query, DAX, Azure Data factory, etc.
  • Proficiency in SQL language, database development & management, ecosystems.
  • Experience with product BOM, engineering documentation, and change control.
  • Experience with PLM/ERP systems (SAP, Oracle), including data structure, storage and configuration.
  • Mathematical, statistical, and analytical skills – able to analyze, model and interpret data, identify trends and patterns to develop insights from data.
  • Knowledge of electronic components is desirable (ICs, actives, passives, electromechanical), including key parametrics and characteristics, commodity hierarchies and classifications, manufacturer/supplier market.
  • Project management skills is desirable – able to lead cross-functional data initiatives from requirements gathering through implementation.
  • Adaptive with strong initiatives, attention-to-detail with a passion for data accuracy, consistency and governance.

Additional Information

XP Power provides a safe and healthy working environment that is stimulating and collaborative, where employees are empowered to make a real difference. We place our people at the heart of everything we do. We understand that if we provide our people with the ultimate experience, they will provide the ultimate experience to our customers. 

Top Skills

Azure Data Factory
Ms Power Query
Oracle
Power BI
Python
SAP
SQL
Tableau

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