About the Team – Supply Chain Operations

The Supply Chain Operations team plays a critical role in enabling the end-to-end supply chain ecosystem. We are responsible for managing key business processes and supporting the development and execution of capabilities that enhance operational efficiency, accuracy, and responsiveness. Our team is collaborative, data-driven, and focused on delivering value through continuous improvement and strategic planning.

Job Summary

The Senior Manager – Facility Engineering & Asset Management Insights is a hybrid leadership role responsible for driving Operational Insights, Engineering, Automation, and Asset Lifecycle Management across Target’s supply chain network, with a strong focus on 4-wall operations.
This role combines data-driven decision making with deep engineering and operational expertise, leading teams across analytics, facility engineering, and automation domains. The position is responsible for building and scaling insights capabilities, Facility Operations and automation solutions that improve safety, throughput, asset performance, and operational efficiency.

The Senior Manager will lead teams of Data professionals and solution experts, drive global partnerships, challenge the status quo, and deliver enterprise-scale solutions through strong technical acumen, strategic thinking, and people leadership.

Based in TII, the role partners closely with global stakeholders, internal technology teams, and third-party integrators deliver enterprise-scale engineering solutions while ensuring compliance with safety, security, and engineering governance standards.

Key Responsibilities

• Lead and develop cross-functional team comprising Data and Engineering professionals.
• Execute strategies for analytics, automation, and engineering aligned with supply chain objectives.
• Drive data-driven insights, reporting, and analytical product development to improve 4-wall operations.
• Manage asset lifecycle, system reliability, and performance optimization initiatives.
• Establish robust project management practices including Agile methodologies and stakeholder communication.
• Partner with global leadership, site operations, and external vendors to deliver scalable solutions.
• Partner with technology teams to oversee server management, DevOps operations, and system reliability for automation platforms.
• Provide subject matter expertise in controls systems, automation software, and material flow optimization
• Drive innovation through advanced analytics, AI/ML, and automation technologies.
• Lead problem solving, root cause analysis, and continuous improvement initiatives.
• Build strong data architecture, Insights frameworks, and visualization capabilities.
• Foster a high-performance culture with focus on collaboration, learning, and operational excellence.
• Manage hiring, talent development, performance, and retention across analytics and engineering teams.
• Communicate engineering strategies, risks, and trade-offs clearly to senior leaders and cross-functional partners.
• Coach, mentor, and develop team members, supporting technical depth, leadership growth, and career progression.

Mandatory Requirements

• Bachelor’s degree in engineering or a related technical field (or equivalent experience).
• 8+ years of overall experience with 5+ years in Supply Chain / Retail Operations
• Proven experience leading engineering teams and delivering enterprise-scale automation solutions.
• Experience in managing team working across the 4-wall operation in field or HQ.
• Hands-on experience with Python, R, SQL, or similar technologies
• Strong problem-solving, critical thinking, and decision-making skills.
• Experience working with vendors, system integrators, and cross-functional internal teams.
• Ability to balance strategic vision with hands-on technical execution in a complex environment.
• Strong communication and influencing skills across multiple organizational levels.

Preferred Requirements

• Experience with DevOps or system reliability engineering in industrial environments.
• Experience in collaborating with Product, Data Engineering and Analytics CFT team.
• Exposure to AI/ML applications in supply chain or engineering domains.
• Experience working in large-scale distribution, logistics, or manufacturing environments.