Technical Director - (Enterprise Data & Analytics Leadership)

Technical Director Data ( Enterprise Data & Analytics Leadership)

Location: Oak Brook, IL

Work Arrangement: Hybrid

Contract: 12 Months with Possible Extension

ABOUT THE ORGANIZATION

Our client is a Fortune 500, publicly traded global ingredient solutions company that turns corn, tapioca, potatoes, stevia, grains, fruits, and other plant-based materials into value-added ingredients for the food, beverage, brewing, animal nutrition, and industrial markets. With roots dating back more than a century, the organization generates several billion dollars in annual net sales, employs more than 11,000 people across manufacturing sites and innovation centers worldwide, and serves customers in over 120 countries.

The organization's growth strategy centers on clean-label reformulation, sugar reduction, plant-based proteins, texturizing solutions, and sustainability-driven innovation. Delivering on that strategy at global scale depends on a modern, connected enterprise data foundation spanning R&D and formulation, manufacturing and plant operations, supply chain and logistics, quality and regulatory/traceability, and commercial analytics across dozens of countries and business units.

THE OPPORTUNITY

We are hiring an accomplished Technical Director Data to lead the client's enterprise data organization and a broad portfolio of data programs, data modernization, enterprise analytics, and data technology initiatives.

This is a senior leadership role operating across multiple business functions, complex global data environments, and multiple technology vendors. The Technical Director will set strategic direction, provide technical leadership, and own delivery oversight for enterprise data initiatives - partnering closely with business and technology leadership to turn the organization's data assets into a durable competitive advantage.

KEY RESPONSIBILITIES

Lead the enterprise Data organization and portfolio across multiple business functions - including R&D/formulation, manufacturing and plant operations, supply chain and logistics, quality/regulatory, and commercial - and the data programs that support them.

Drive data modernization and transformation across platforms, architecture, integration, and analytics, unifying data from global manufacturing sites, SAP and other ERP systems, and commercial applications into a coherent enterprise data foundation.

Own the data strategy behind supply chain and logistics visibility - demand planning, inventory, freight, and distribution - turning fragmented operational data into a single, trusted source of truth.

Provide technical leadership across a diverse portfolio of enterprise data and analytics programs, including Power BI and other BI/reporting platforms used across manufacturing, supply chain, and commercial teams.

Manage and coordinate multiple technology vendors, implementation partners, and delivery teams across a complex, multi-country technology landscape spanning 120+ countries.

Set enterprise-level direction across data architecture, cloud platforms (Azure and GCP), integration, governance, data quality, and analytics - balancing global standardization with the needs of regional and functional stakeholders.

Partner with business and technology leaders to translate business priorities into scalable, well-governed data solutions that support supply chain visibility, plant performance, and go-to-market analytics.

Drive standardization, modernization, and simplification across the enterprise data landscape, reducing technical debt and vendor sprawl.

Evaluate emerging data technologies - including use cases for R&D, quality, and supply chain operations - and identify opportunities to convert them into measurable business value.

Lead, mentor, and develop data and analytics teams, strengthening technical capability and succession depth across the organization.

REQUIRED QUALIFICATIONS

20+ years of experience in Data, Analytics, or Technology leadership roles, with significant experience leading enterprise data organizations or large-scale data portfolios.

Proven experience operating across multiple business functions, complex data programs, and multiple technology vendors - ideally within a global manufacturing, CPG, or process-industry environment.

Strong background in data modernization, enterprise analytics, data platforms, and data technologies at enterprise scale, including ERP (SAP preferred) and BI/reporting tools such as Power BI.

High-level command of enterprise data architecture, cloud platforms, data integration, analytics, governance, and security.

Proven track record leading large-scale technology transformation and modernization programs, including vendor selection and delivery oversight.

Ability to operate at both strategic and technical levels, communicating effectively with executive, business, and technical stakeholders across a global organization.

Strong leadership, vendor management, program management, and stakeholder management skills.

TECHNICAL DEPTH ACROSS THE DATA STACK

Candidates should bring demonstrated, hands-on-to-strategic experience across three layers of the enterprise data stack:

Layer 1 Governance: Data governance, stewardship, master data management, cataloging, and standards that keep enterprise data trusted, consistent, and well-defined across business functions.

Layer 2 Analytics: Business intelligence, reporting, and advanced/predictive analytics (e.g., Power BI) that turn governed data into decisions for supply chain, plant operations, and commercial teams.

Layer 3 Data Engineering: Data platforms, pipelines, integration, and cloud architecture (Azure/GCP, SAP and other source systems) that reliably move and prepare data at enterprise scale.

PREFERRED QUALIFICATIONS

Experience in a global, multi-business enterprise - food, beverage, CPG, agriculture, or other process-manufacturing industries strongly preferred.

Hands-on familiarity with supply chain and logistics data and systems (demand planning, inventory, transportation/distribution).

Experience with modern cloud data platforms - Microsoft Azure and/or Google Cloud Platform (GCP) - and enterprise ERP landscapes (e.g., SAP), plus BI tools such as Power BI.

Exposure to AI/ML, Generative AI, and other emerging data technologies, with a point of view on responsible, value-driven adoption.

Bachelor's or Master's degree in Computer Science, Engineering, Information Technology, Data Science, or a related field.