Senior Solution Architect - Data Engineering

About the Role

The Supply Chain (SC) Data Strategy Consultant is Bristlecone's Data & AI. This role leads the SC Data Strategy offering end-to-end: conducting maturity assessments, building Data & AI architecture blueprints, and delivering executable roadmaps that position clients to adopt GenAI and Agentic AI across their SC operations. Beyond direct delivery, each engagement generates qualified pipeline for the broader offering portfolio while embedding Bristlecone as the client's trusted SC Data & AI partner.

What You'll Do

• Lead SC Data Strategy engagements end-to-end — from stakeholder discovery and maturity assessment through SC Data & AI architecture blueprint, implementation roadmap, governance model, and delivery plan
• AI-first framing: Engage CXO audiences on SC data strategy for AI enablement, platform investment decisions, and implementation roadmap prioritization — framing every data investment in terms of the AI outcomes it unlocks
• AI use case identification: Identify and prioritize Classical AI, GenAI and Agentic AI use cases within each client's SC program — demand sensing copilots, autonomous supply exception management, AI-powered supplier onboarding, and intelligent SC reporting
• AI-ready architecture: Design Data & AI architecture blueprints that set the foundation for Agentic AI adoption — ensuring platform choices, data product designs, feature store architectures, and governance models are AI-ready from day one
• Build and continuously enrich Bristlecone's proprietary SC data maturity benchmark database from anonymized engagement outputs — the hard-to-replicate asset that differentiates Bristlecone from other firms
• GenAI in delivery: Leverage GenAI tooling actively in your own delivery workflow — AI-assisted maturity assessment synthesis, LLM-powered roadmap generation, and AI-augmented stakeholder interview analysis to compress delivery timelines
• Conduct SC regulatory applicability assessments across CSRD, EUDR, UFLPA, and CBAM as part of the governance model deliverable
• Contribute to offering IP development — refining the assessment methodology, benchmark scoring model, and deliverable templates based on engagement experience; building AI evaluation criteria into the SC data maturity framework
• Support GTM initiatives: contribute to proposals, present at C-suite client workshops, and represent Bristlecone at key industry events as needed
• Mentor and develop SC Data Architecture Consultants and Data Governance Consultants within the Strategy & Advisory cluster — specifically on AI-augmented delivery practices

What You'll Bring

• 8-12 years of experience in supply chain, SC analytics, or SC data — with a track record spanning both strategy and execution, not advisory alone
• Prior seniority as an SC data strategist, or SC consulting manager at a Global 2000 company or consultancy
• SC platform landscape: Deep knowledge of SAP IBP/APO, Kinaxis RapidResponse, Blue Yonder, Oracle SCM Cloud — and critically, how data from each platform feeds downstream AI/ML use cases and Agentic AI workflows
• AI & data architecture: Working knowledge of cloud data and AI platform stacks: Databricks (Unity Catalog, MLflow, AI Functions), Snowflake (Cortex AI), Microsoft Fabric (Azure OpenAI integration), GCP (Vertex AI, BigQuery ML) — able to recommend the right AI-ready data stack for each client's SC context
• GenAI fluency: Practical understanding of large language models, prompt engineering, AI agents, and Agentic AI frameworks — able to have a substantive conversation with a CDO about what GenAI can and cannot reliably do in an SC context today
• Experience designing SC data governance frameworks, Data & AI implementation roadmaps, and AI readiness assessments that practitioners adopt
• Strong executive facilitation and communication skills — able to frame Data & AI investment decisions in language that resonates with CXOs.
• Create thought leadership on SC AI, SC data strategy, or Agentic AI in supply chain

Bonus If You Have

• Hands-on GenAI / Agentic AI: Experience implementing GenAI or Agentic AI in SC contexts — demand sensing copilots, autonomous exception management agents, AI-powered supplier onboarding, or LLM-based SC reporting assistants
• Familiarity with Agentic AI frameworks: LangChain, LangGraph, Microsoft AutoGen, CrewAI, or equivalent — applied to real SC automation workflows
• Track record of building AI-ready data foundations: feature stores, vector databases, semantic data layers, or SC-specific AI model registries
• SC regulatory depth: CSRD Scope 3 methodology, EUDR due diligence workflows, UFLPA audit requirements, or CBAM embedded carbon data obligations
• Published thought leadership on SC AI, SC data strategy, or Agentic AI in supply chain