Director of Data and AI

The Director, AI & Data leads the Campbell Companies Center of Excellence (CoE) for data, AI, automation, and software engineering. This role is accountable for the enterprise data platform, data engineering, data governance, AI and agentic AI governance, automation, software development, and data and AI enablement across Campbell Companies and Wheeler Machinery. The Director builds and leads the operating model, organization, and platform that turns trusted data into governed AI and measurable business outcomes.

The Director operates as a peer to the Director of Information Technology, collaborating closely on shared infrastructure, security, and end-user delivery while maintaining clear ownership of the data, AI, and automation domain. This is a foundational leadership role, critical to Campbell Companies’ digital transformation strategy.

• Define and execute the AI & Data strategy, multi-year roadmap, and operating model for Campbell Companies, aligned to business priorities and value targets.
• Design and evolve the CoE organizational framework across data engineering, data platform, AI and agentic solutions, automation, software engineering, and data enablement, with clear ownership, intake, prioritization, and service-level expectations.
• Establish and enforce enterprise standards, architecture review, and decision rights so that business-unit and vendor-led work follows CoE guardrails no ungoverned shadow AI, shadow data, or shadow automation.
• Define KPIs and value-realization reporting (adoption, cost, quality, risk, and business outcomes) and present the AI & Data roadmap, governance posture, and results to the VP of Digital quarterly.

• Own the enterprise data platform built on Microsoft Fabric: medallion Lakehouse architecture (Bronze/Silver/Gold), One Lake governance, Fabric Data Factory, Real-Time Intelligence, and Power BI semantic models.
• Set architecture standards for ingestion, transformation, modeling, and serving, including reusable patterns, data contracts, and domain-aligned data products.
• Govern One Lake naming conventions, workspace design, partitioning, shortcuts, and access patterns.
• Manage Fabric capacity, performance, and cost (Fin Ops), including capacity planning, workload isolation, and chargeback or showback.
• Integrate enterprise source systems (ERP, finance, service, parts, telematics, and equipment data) into a consistent, governed analytical foundation.

• Lead data engineering practices: pipeline development, orchestration, testing, version control, and CI/CD for Fabric and Azure data assets.
• Operate the data platform as a product, with defined SLAs, monitoring, observability, incident response, and root-cause management.
• Embed data quality, lineage, and catalog management into all pipeline operations, with automated validation at each medallion layer.
• Drive platform engineering and infrastructure-as-code standards in partnership with the Director of IT.

• Own the data governance framework: data ownership and stewardship, business glossary, certified datasets, master and reference data, retention, and classification (e.g., Microsoft Purview).
• Implement role-based, row-level, and column-level security and sensitivity labeling in partnership with Information Security.
• Ensure compliance with applicable data privacy and AI regulations, customer and OEM/partner data agreements, and internal audit requirements.

• Establish and enforce AI governance: use case registry, risk classification, approved tool and model standards, and sunset criteria.
• Align the governance…