Senior Supply Chain Analytics Engineer

Senior Supply Chain Analytics Engineer

Livingston, NJ / New York, NY / Sunnyvale, CA / San Francisco, CA / Bellevue, WA Core Weave is The Essential Cloud for AI™. Built for pioneers by pioneers, Core Weave delivers a platform of technology, tools, and teams that enables innovators to build and scale AI with confidence. Trusted by leading AI labs, startups, and global enterprises, Core Weave combines superior infrastructure performance with deep technical expertise to accelerate breakthroughs and turn compute into capability.

Founded in 2017, Core Weave became a publicly traded company (Nasdaq: CRWV) in March 2025. Learn more at

What You'll Do:

The Supply Chain Strategy & Transformation (SCST) team is responsible for designing and scaling the operating model for how Core Weave plans, sources, builds, and delivers data center capacity for our customers. We partner closely with Supply Chain, Product Engineering, Data Center Operations, and the Enterprise Engineering teams to turn strategy into execution and measurable impact.

This position sits within the Data Strategy within SCST, responsible for turning operational data from Plan, Source, Build, Deliver, Quality and Sustain into the analytics, models, and tooling that drive faster, better supply chain decisions.

About the Role:

We are seeking an experienced Analytics Engineer to join our Supply Chain Data Strategy team. In this hands-on role, you will partner closely with the IT Data Engineering team and the upstream Operational business owners to design and build scalable data pipelines, models, and dashboards that give supply chain leaders visibility into business health metrics such as spend, lead times, and on-time performance across the network.

You will serve as the technical bridge between raw supply chain data and the leadership decisions by turning messy, fragmented data into trusted, actionable insight. This role reports to the Head of Supply Chain Data Strategy and is based out of any one of our locations at Sunnyvale, CA, Livingston, NJ, Dallas, TX or Bellevue, WA.

In This Role You Will:

• 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.

Who You Are:

• 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, Big Query, 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.
• Prof…