Supply Chain Analytics Engineer

CoreWeave is The Essential Cloud for AI™. Built for pioneers by pioneers, CoreWeave delivers a platform of technology, tools, and teams that enables innovators to build and scale AI with confidence.

• Design, build, and maintain data pipelines that ingest and transform supply chain data from ERP, procurement, logistics, and planning systems into analytics-ready datasets.
• Develop dashboards and reporting tools (e.g., Tableau, Power BI, Looker or 1P platforms) that track key supply chain KPIs such as lead time, supplier performance, spend, inventory, and capacity utilization.
• Build and maintain data models that support forecasting, scenario planning, and network capacity analysis.
• Partner with Master Data Governance to ensure analytics are built on clean, well-governed item, vendor, and location data.
• Collaborate with Procurement, Logistics, Warehousing, Planning, and DC Ops teams to translate business questions into analytical solutions.
• Automate recurring reporting processes to reduce manual effort and improve data accuracy and timeliness.
• Identify data quality issues and gaps in existing systems, and work cross-functionally to resolve root causes.
• Support supply chain projects (ERP implementations, system upgrades, migrations) as the analytics and reporting workstream lead.
• Present analytical findings and recommendations to senior leadership in a clear, actionable format.
• Continuously evaluate and recommend new tools, technologies, and best practices to improve the team’s analytics capabilities.

• 8-12 years of hands-on experience in data analytics, analytics engineering, or business intelligence within a supply chain, procurement, or operations environment.
• Strong proficiency in SQL and experience with a modern data warehouse (Snowflake, BigQuery, Redshift, or similar).
• Experience building and maintaining ETL/ELT pipelines using tools such as dbt, Airflow, Fivetran, or equivalent.
• Proficiency with a BI/visualization tool (Tableau, Power BI, Looker or 1P platform) and a track record of building dashboards that leadership actually uses.
• Working knowledge of Python or another scripting language for data manipulation and automation.
• Familiarity with supply chain data domains: materials/items, vendors, purchase orders, logistics, Quality and inventory.
• Proficiency in or exposure to ERP systems (SAP S/4HANA, SAP ECC, Oracle NetSuite, or equivalent).
• Solid analytical skills with the ability to perform root cause analysis and translate data into a clear business narrative.
• Excellent communication skills; ability to present complex data concepts to non-technical audiences.
• Preferred: Experience with data quality and governance tools (Informatica, Collibra, Alation, Atlan, or similar); experience applying agentic AI/LLM-based tools to analytics workflows; experience building forecasting or optimization models for supply chain or logistics networks; experience supporting global supply chain operations in Data Center Build; familiarity with statistics or machine learning techniques applied to operational data; project management experience (PMP or Agile certification a plus).