Collect, analyze, and visualize supply chain performance data (inventory turns, delivery performance, lead times, capacity utilization, material availability, etc.) to support operational and strategic decisions
Partner with Supply Chain, Operations, and IT teams to translate business needs into data models and metrics that measure process health and efficiency
Develop and maintain self-service dashboards and KPIs that enable users to monitor key performance indicators
Perform data validation, reconciliation, and root-cause analysis for discrepancies in system reports, ensuring accuracy across ERP and BI tools
Create and maintain data pipelines and queries (e.g., via SQL, Power Query, or SAP extractors) to automate recurring reports and reduce manual effort
Support data quality initiatives by identifying errors, proposing corrective actions, and coordinating with data owners to improve master data governance
Provide ad-hoc analysis and scenario modeling to evaluate changes in demand, supply, or logistics assumptions
Assist in process documentation and help standardize analytic procedures, data definitions, and reporting templates
Collaborate on continuous improvement initiatives, using data to identify bottlenecks and recommend automation or process optimization opportunities
Participate in testing and validation of system updates or new data tools to ensure alignment with reporting and analytics need
Job Requirements:
3-5 years of experience in data analysis, business intelligence, or ERP-driven supply chain processes (planning, procurement, logistics, or manufacturing).
Hands-on experience with data visualization tools (Power BI or Tableau) and data transformation tools (Power Query, Alteryx, or Python for analytics).
Working knowledge of ERP reporting and data structures, preferably in SAP
Ability to extract and interpret data using SQL, Excel (PowerPivot, PowerQuery), or similar tools.
Understanding of supply chain metrics (inventory accuracy, on-time delivery, demand forecast accuracy, supplier performance, etc.) and how to measure them.
Familiarity with data governance principles, master data management, and reporting hierarchies.
Strong analytical and critical thinking skills capable of turning data into clear, actionable insights.
Detail-oriented, organized, and comfortable managing multiple priorities.
Clear communicator able to present findings to both technical and business stakeholders.
