Senior Supply Chain Analytics Engineer

CoreWeave•Sunnyvale, CA

6h•$157,000 - $210,000•Hybrid

About The Position

The Supply Chain Strategy & Transformation (SCST) team is responsible for designing and scaling the operating model for how CoreWeave 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. 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.

Requirements

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.

Nice To Haves

Experience with data quality and governance tools (Informatica, Collibra, Alation, Atlan, or similar).
Experience applying agentic AI/LLM-based tools to analytics workflows (e.g., building or using AI agents for automated data QA, natural-language querying of supply chain data, self-serve reporting, or pipeline monitoring);
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).

Responsibilities

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.