Anduril Industries is looking to enhance its digital landscape and increase efficiencies throughout its end-to-end supply chain processes.
Requirements
- Proficiency in data visualization and reporting tools such as Tableau, Power BI, or similar.
- Experience in large-scale implementation of ERP, Oracle highly preferred.
- Experience with database management and data analysis software, such as SQL, Excel, or other analytical tools.
- Strong understanding of developing and defining dashboards and KPI's for supply chain operations.
- Experience working with supply chain IT systems and data analytics.
- Experience developing, documenting and executing supply chain focused digital ecosystems.
Responsibilities
- Support and execute functional process and data maps for Supply Chain within Procurement, Purchasing, Program Management, Material Management, etc.
- Collaborate with IT teams to execute agreed-upon enhancement roadmap to deliver critical business value.
- Act as one of the main SMEs/PoCs for System, Process and Data roadmap for Supply Chain Operations.
- Scope and deploy a Supply Chain Reporting/KPI suite, including both supply partner facing and internal KPI dashboards.
- Work with IT teams in defining requirements for home-grown applications and platforms.
- Lead the business end of development-to deployment, ensuring design with focus on critical business capabilities and a high degree of usability, efficiency, automation and integration into the larger system and process landscape.
Other
- B.S. in engineering, supply chain or equivalent degree.
- 8+ years of experience with supply chain IT systems and data analytics.
- Master's degree in data analytics, supply chain management, or related field (preferred).
- Strong communication and collaboration skills (throughout all levels of the organization and across multiple business/functional verticals).
- Excellent communication skills, with the ability to convey complex data in a clear and actionable manner to various audiences.
- Attention to detail and commitment to accuracy in data reporting and analysis.
