Component Engineer – Data Analytics (Based in Singapore)
XP Power Lihat semua pekerjaan
- Ipoh, Perak
- Tetap
- Sepenuh masa
- 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.
- 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.
- Knowledge of electronic components (ICs, actives, passives, electromechanical), including key parametrics and characteristics, commodity hierarchies and classifications, manufacturer/supplier market.
- 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 analyse, model and interpret data, identify trends and patterns to develop insights from data.
- Project management skills - 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.