Director, Supply Chain Lead Data Architect

Job Description

Summary:

The Supply Chain Lead Data Architect will own the supply chain data model and the data-product architecture that enables trusted analytics, decision intelligence and data science across the North America Operating Unit. This leader will treat data as a product: defining the business purpose, consumers, ownership, quality expectations, access patterns, lifecycle and measurable value of the data assets the organization depends on.

The role combines supply-chain domain mastery with enterprise data modeling, platform product strategy and modern engineering fluency. Partnering with supply chain, product, analytics, data science, Global Data and AI, Enterprise Architecture, Security, Governance and platform teams, the successful candidate will translate business decisions into interoperable, secure, governed and reusable data capabilities that improve performance and deliver measurable business value. This is a Director-level role.

About the Role Own Supply Chain Data Products and Enterprise Data Models Define and execute the supply chain data-product strategy and multi-year architecture roadmap that enables analytics, reporting, decision intelligence and data science.

Develop and own the canonical supply chain data model, including conceptual, logical and physical models, shared business definitions and semantic layers for domains such as demand, supply, inventory, manufacturing, logistics, customer service and performance.

Establish reusable patterns for data products, ingestion, integration, lakehouse and warehouse platforms, APIs, events and streaming, master and reference data, semantic models, analytics and data-science consumption.

Lead architecture reviews and technology decisions, balancing decision value, interoperability, scalability, security, quality, reliability, performance, cost and speed to market.

Enable Integration Interoperability and Modern Data Engineering Connect supply chain data requirements with enterprise platforms, applications and standards, reducing duplicate data, fragmented definitions, point-to-point integrations and technical debt.

Define integration and interoperability standards across ERP, manufacturing, warehouse, transportation, planning, customer and external-partner systems using APIs, events, common identifiers and governed data contracts.

Set engineering standards for CI/CD, Infrastructure as Code, automated testing, orchestration, observability, metadata, lineage, data quality, reliability and operational support.

Drive reusable frameworks, platform capabilities and product operating practices that accelerate delivery and make data easy to discover, understand, access and use responsibly.

Improve workload performance, resilience and cost efficiency across cloud data, analytics and data-science platforms.

Translate Business Decisions into Data Requirements Work with supply-chain leaders to identify the decisions that matter most, the measures that define success and the data required to improve planning, service, cost, inventory, capacity, resilience and sustainability outcomes.

Convert business priorities into clear data requirements, data-product backlogs, domain models, data contracts, acceptance criteria and delivery roadmaps that technical teams can execute.

Define patterns that enable data scientists and analysts to use governed, explainable and fit-for-purpose data, including feature-ready data, semantic models and secure self-service access.

Partner with data science and engineering teams to move analytical and predictive solutions from prototypes to secure, observable and reliable production capabilities.

Establish architecture guardrails for privacy, security, governance, model use, explainability, evaluation and appropriate human oversight where AI is applied.

Lead Cross Functional Delivery and Augmented Teams Serve as a trusted partner to supply-chain, product, finance, operations, data science and technology leaders; communicate architecture choices, dependencies, tradeoffs, value, cost and risk in clear business language.

Lead cross-functional teams and augmented resources, setting clear outcomes, architectural guardrails, delivery expectations and quality standards while building capability in internal teams.

Facilitate alignment across organizational boundaries, resolve design decisions and sequence investments to deliver the highest-value data products first.

Improve the discoverability, accessibility, quality and usability of trusted supply-chain data so…