IT Business Partner
Posted 25 Sep 2026
Advertised as “Senior Manager, IT Business Partner”
BranchFactor Summary
The original posting with the fluff stripped out
- Level
- Band 11
- Expected experience
- 7+ yrs
- Management level
- Individual contributor
No salary listed for this role.
Field of studyBusiness Administration, Commerce, Engineering, Information Technology
Study levelBachelor's
11 - Senior Manager, IT Business Partner
Req ID: 137924
Remote Position: No
Hiring Manager: Osgood Vogler
Band: 11
Region: Asia
Country: Thailand
State/Province: Chonburi
City: Laem Chabang
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.
General Overview
Functional Area: Information Technology (ITM)
Career Stream: IT Partnership (PTN)
Role: Senior Manager (SMG)
Job Title: Senior Manager, IT Business Partner
Job Code: SMG-ITM-BUSP
Job Level: Band 11
Direct/Indirect Indicator: Indirect
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.