Role: Senior Supply Chain Solutions Analyst
Location: Sunnyvale, CA (Hybrid, 3 days a week)
Role Summary
We''''re looking for a senior solutions analyst to build internal tools and deliver data-driven analyses that power Meta''''s supply chain risk intelligence program. Think "forward-deployed engineer", you''''ll sit embedded with the Strategic Sourcing team, understand their problems firsthand, and build the last-mile applications and analyses they actually use.
This isn''''t a platform or infrastructure role. Your job is to take messy real-world supply chain data - BOMs, supplier records, component lifecycle information - and turn it into clean, validated datasets and working internal tools that help sourcing managers make faster, better decisions.
What You''''ll Do
Data Validation & Analysis
· Validate and cleanse internal BOM (Bill of Materials) and MPN (Manufacturer Part Number) data across systems
· Cross-reference supplier data against external sources (Z2Data, DigiKey, SiliconExpert) to identify gaps, risks, and inconsistencies
· Build automated data quality checks and exception workflows
· Deliver ad-hoc analyses, e.g., "which components in this program have lifecycle risk?" or "where are we single-sourced on long-lead parts?"
Internal Tools & Applications
· Build and iterate on custom internal tools for supply chain risk monitoring (Python, web-based dashboards, APIs)
· Integrate external market intelligence platforms into internal workflows
· Develop AI-assisted features - risk scoring, lifecycle classification, early warning signals
· Create self-service analytics and visualizations for non-technical sourcing leads
Solution Design
· Translate supply chain business problems into technical solutions
· Prototype fast - get a working tool in front of users within days, not months
· Work with existing data infrastructure (pipelines, tables, etc) rather than building from scratch
· Identify opportunities to automate manual processes with AI/LLM tools
Required Skills
· 5+ years in a technical analyst, solutions engineer, or applied data science role
· Strong Python - scripting, data manipulation (pandas), API integrations, light web development
· Proficient in SQL — can query large datasets, write complex joins, work with partitioned tables
· Experience connecting to and working with external APIs and data sources
· Ability to build working internal tools quickly - web apps, dashboards, notebooks, scripts
· Comfortable working with messy, real-world data - reconciling across sources, handling edge cases
· Strong communication — can present findings to non-technical stakeholders clearly
Nice to Have
· Supply chain, procurement, or hardware operations background
· Familiarity with electronic component data (BOMs, AVLs, MPNs, lifecycle stages)
· Experience with component databases (DigiKey, Octopart, Z2Data, SiliconExpert)
· Comfort with AI/ML tools - LLMs, classification models, or using AI assistants to accelerate work
· Web frameworks (Flask, Streamlit, React) for rapid prototyping
· Meta internal tools (Bento, Presto/Hive, Unidash, Dataswarm) or equivalent at scale