Senior Supply Chain Solutions Analyst

Role: Senior Supply Chain Solutions Analyst

Location: Sunnyvale, CA (Hybrid, 3 days a week)

Full Time Only

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