Senior Manager, IT Business Partner

Summary

The Senior Manager, IT Business Partner serves as the strategic interface between the Manufacturing/Operations organization and the Global IT team, specifically driving AI, Data, and Analytics transformations. Leads the identification, evaluation, and deployment of AI use cases across manufacturing operations. This is not a purely advisory role; you are the architect of requirements. You will spend your time embedded in operations, diagnosing complex physical and digital bottlenecks, and translating them into ironclad technical system requirements, data schemas, and functional specifications for AI/ML models. Your mission is to turn operational data into measurable improvements in Operations KPIs.

Detailed Description

Performs tasks such as, but not limited to, the following:

Initiative Qualification & Solution Design

• Embed with Operations: Partner closely with senior Operations leaders to deeply understand their workflows, pain points, and legacy systems.
• Translate Business to Tech: Convert high-level operational goals into detailed functional and technical requirements for Data professionals. Produce high-quality documentation and functional prototypes to translate vague business desires into actionable references.
• Opportunity Identification: Evaluate operational processes to identify high-value AI use cases, such as predictive maintenance, computer vision for defect detection, demand forecasting, and dynamic scheduling.
• Feasibility Assessment: Analyze existing data infrastructure on the shop floor to determine if the velocity, variety, and volume of data can actually support an AI solution.
• Define AI Inputs/Outputs: Explicitly map out the data pipelines required for models — defining what IoT sensor data, historical logs, or image feeds are needed as inputs, and how the model's output should integrate back into operational systems.
• Solution Architecture: Grasp complex, integrated IT architectures and evaluate how these systems enable or constrain specific business processes in a high-velocity manufacturing environment.
• Proof of Concept (POC) Governance: Develop and manage prototypes and POCs to test and evaluate AI capabilities and their ability to drive tangible benefits in mfg ops. Apply clear decision criteria to determine whether to scale or exit a POC.

Program Management & Execution Oversight

• Portfolio Governance: Act as the primary point of oversight for all in-flight IT projects within the manufacturing and operations landscape.
• Data & AI Governance: Act as the primary point of oversight for data-driven projects, ensuring compliance with global IT standards and security controls.
• Escalation Management: Serve as the first point of escalation for project roadblocks, ensuring that risks to timeline, budget, or scope are mitigated including data gaps, infrastructure dependencies, and model deployment hurdles.
• Stakeholder Communication: Work closely with IT Project Managers to provide regular, transparent updates to business leaders on the status of the technology portfolio.
• Operational Readiness: Ensure organizational change management (OCM) is integrated into project delivery, including training plans, procedure updates, and communication

Strategic Stakeholder & Relationship Management

• Executive Partnership: Develop and maintain strong relationships with senior leaders in Operations, Finance, and Supply Chain. Fosters a data-driven culture and advocates for the value of AI and analytics in manufacturing.
• Roadmap Alignment: Facilitate ongoing discussions to align the IT roadmap with the business’s long-term growth plans, including site expansions and digital factory transformations. Assess and evolve the orgnization's data maturity, helping the business transition from reactive reporting to predictive and prescriptive analytics.
• Industry Trends: Proactively monitor and share innovations in Industrial AI, edge computing, and manufacturing data standards to keep Celestica at the forefront of digital factory transformation.
• IT Integration: Maintain a profile of all IT integration touchpoints (internal and external) between Celestica and its key customer accounts.
• Smart Factory / Automation: Partner with the internal Digital Factory team to deploy automation equipment and IoT solutions on the shop floor.
• Supply Chain & Warehouse: Oversee the integration of data from various relevant partners to support AI use cases

Knowledge/Skills/Competencies

• Business Acumen: Deep understanding of electronics manufacturing, supply chain management, and regulatory environments (Aerospace & Defense, HealthTech).
• The "Translator" Skillset: Proven ability to take an ambiguous operational problem, break it down into data requirements, and communicate effectively with both a front-line factory supervisor and a Data Scientist.
• Technical Literacy: Solid understanding of the AI/ML lifecycle (data ingestion, training, deployment, monitoring). You don't need to code the algorithms, but you must understand how data pipelines, computer vision, and predictive modeling work structurally.
• Domain Expertise: Strong background in manufacturing operations, supply chain logistics, or industrial IoT (IIoT). Familiarity with systems like SAP, Manufacturing Execution Systems (MES), and SCADA is highly preferred
• Financial Literacy: Understanding of manufacturing finance, including ROI calculation, Capital Expenditure (CapEx) vs. Operating Expenditure (OpEx) planning, and the ability to defend the financial merits of a technology investment
• Strategic Communication & Exec