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Senior Supply Chain Solutions Analyst
Bellatrix Systems LLCCA🇺🇸United StatesPosted 10 Aug 2026
Quick Overview
Work Type
Hybrid
Level
Mid Senior
Job Description
Role: Senior Supply Chain Solutions Analyst
Location: Sunnyvale, CA (Hybrid, 3 days a week)
Location: Sunnyvale, CA (Hybrid, 3 days a week)
Full Time
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
Working Style
Embedded with the sourcing team, you understand the business problem before you write code
Ship fast, iterate often - working tools in days, polished in weeks
High autonomy - own your solutions end-to-end
Collaborative - work closely with the XFN team, Supply Chain Transformation data engineers, and sourcing pillar leads
Comfortable with ambiguity, half the value is figuring out what to build
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
Working Style
Embedded with the sourcing team, you understand the business problem before you write code
Ship fast, iterate often - working tools in days, polished in weeks
High autonomy - own your solutions end-to-end
Collaborative - work closely with the XFN team, Supply Chain Transformation data engineers, and sourcing pillar leads
Comfortable with ambiguity, half the value is figuring out what to build
Skills
Procurement
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