We are seeking a hands-on data and reporting specialist with a strong background in database architecture, data modeling, and reporting cube design to support our global Supply Chain Management (SCM) reporting landscape. In this role, you’ll be responsible for building and optimizing the data backbone that powers SCM reporting — from data integration and cube modeling to ensuring data quality and performance across multiple global systems. You’ll work closely with IT and data governance teams to design scalable, reliable, and efficient data flows that enable consistent and accurate reporting across the organization.
- Design and develop SCM reporting databases, data models, and cubes to support global analytics and KPI reporting.
- Specify data extraction, transformation, and loading (ETL) processes between ERP, SCM, and reporting systems.
- Collaborate with IT on data architecture, schema design, and performance optimization for reporting and dashboard solutions.
- Ensure data quality, consistency, and integrity across systems through validation, error handling, and standardized data definitions.
- Build and automate interfaces and data pipeline concepts that streamline data flow for SCM reporting tools.
- Evaluate and integrate new data platforms, technologies, and tools to enhance scalability and reporting performance.
- Document reporting concepts and details to ensure transparency and maintainability.
What we look for
- Degree in Computer Science, Information Systems, Data Engineering, or a related field.
- 5+ years of hands-on experience in data architecture, data warehousing, or business intelligence development.
- Deep understanding of relational and multidimensional database design, including data cubes and star/snowflake schemas.
- Experience with reporting technologies (Power BI, SAP BW, Snowflake, Oracle).
- Strong SQL skills and dataflow knowledge
- Familiarity with supply chain data domains (materials, logistics, production, demand, etc.) is a strong plus.
- Self-driven, detail-oriented, and passionate about creating clean, efficient data structures
Please contact Soi Kim Kee for further information via suki.kee@ams-osram.com or +65 () 62402395.