You must possess the below minimum qualifications to be initially considered for this position. Preferred qualifications are in addition to the minimum requirements and are considered a plus factor in identifying top candidates.
Bachelor's/Master's degree in Computer Science, Information Technology, Data Management, or/and 5+ years experience in product master data architecture related to semiconductor manufacturing
Strong communication and collaboration skills, with the ability to lead cross-functional teams
Self-motivated with a strong sense of accountability and ownership
High attention to detail and commitment to data accuracy
Strategic and solution-oriented, with strong analytical and problem-solving skills
5+ years of experience or knowledge with one or more of the following:
Data modeling and data integration
Master data management tools and technologies
Data governance frameworks and best practices
Field Programmable Gate Arrays (FPGAs) products
Job Type:
Regular
Shift:
Shift 1 (Malaysia)
Primary Location:
Penang 15, Penang, Malaysia
Additional Locations:
Posting Statement:
Additional Information
Job Details:
Job Description:
As a Product Master Data Architect, you will be responsible for designing, developing and managing master data architecture for Altera products to ensure high quality, reliable product data as well as alignment with business objectives and strategies.
Key responsibilities include:
Develop data models, definitions, and standards for product master data ensuring compliance with industry standards and company policies.
Establish and enforce data governance policies and procedures to ensure data integrity, quality and consistency across all systems and platforms including ERP, PLM, Supply Planning and Manufacturing systems
Work closely with cross functional business stakeholders including supply chain, engineering and marketing teams to understand product master data requirements and provide solutions.
Identify opportunities to improve data management processes and workflows
Lead cross functional initiatives to continuously improve the data architecture and management processes