Senior Analyst – Facility Engineering & Asset Management

About us: As a Fortune 50 company with more than 400,000 team members worldwide, Target is an iconic brand and one of America's leading retailers. Joining Target means promoting a culture of mutual care and respect and striving to make the most meaningful and positive impact. Becoming a Target team member means joining a community that values different voices and lifts each other up. Here, we believe your unique perspective is important, and you'll build relationships by being authentic and respectful. Overview about TII At Target, we have a timeless purpose and a proven strategy. And that hasn’t happened by accident. Some of the best minds from different backgrounds come together at Target to redefine retail in an inclusive learning environment that values people and delivers world-class outcomes. That winning formula is especially apparent in Bengaluru, where Target in India operates as a fully integrated part of Target’s global team and has more than 4,000 team members supporting the company’s global strategy and operations. 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 Analyst – Facility Engineering & Asset Management is an individual contributor responsible for executing data analytics, reporting, and performance monitoring activities supporting facility engineering, maintenance excellence, and asset lifecycle management across Target’s supply chain network, with a strong focus on 4-wall operations. The role analyzes facility maintenance, asset management, and material handling equipment (MHE) data to identify performance gaps and generate actionable insights related to equipment reliability, asset productivity, maintenance optimization, and operational efficiency. Based in TII, the Analyst partners with global engineering, maintenance, operations, and technology teams to deliver accurate analytical outputs and support data-driven decisions. Key Responsibilities Extract, clean, validate, and analyze data from multiple operational systems to generate actionable insights supporting facility engineering, maintenance, and asset management decisions. Develop, maintain, and enhance dashboards, reports, and analytical solutions using SQL, Python, Power BI, or similar tools to monitor facility and equipment performance. Collaborate with the engineering team and ensure the system uptime is maintained at a certified level to avoid any throughput losses Have an understanding of the engineering aspects of asset functioning to evaluate the maintenance and spare parts details Track and analyze asset health, equipment reliability, maintenance effectiveness, and operational performance across distribution facilities to identify trends and opportunities. Monitor equipment uptime, MTBF, MTTR, preventive maintenance compliance, and maintenance costs to support reliability and maintenance optimization. Consolidate and analyze equipment performance, asset condition, maintenance costs, and investment data to support capital planning, engineering projects, and asset lifecycle decisions. Support automated reporting solutions, analytical models, and visualization capabilities while exploring AI/ML and advanced analytics to improve efficiency and insights generation. Partner with global engineering, maintenance, operations, and technology teams to understand requirements, validate data, resolve issues, and deliver analytical solutions. Independently execute assigned analytical projects and activities, ensuring data accuracy, adherence to established processes, and timely delivery of quality outputs. Prepare and present clear reports, performance insights, and recommendations to the global leadership team and cross-functional stakeholders to support data-driven decision-making. Technical Competencies SQL, Python, R, Power BI, Tableau or similar tools; data extraction, cleaning and validation; advanced Excel; dashboard development and KPI reporting; asset performance and maintenance analytics; reliability metrics systems and material handling equipment. Core Competencies Analytical Thinking | Problem Solving | Execution Excellence | Attention to Detail | Data-Driven Decision Making | Learning Agility | Collaboration | Stakeholder Communication | Ownership & Accountability Mandatory Requirements Bachelor’s degree in Engineering, Data Analytics, Computer Science, Statistics, or a related technical field. 1–3 years of relevant experience in data analytics, business intelligence, engineering analytics, supply chain operations, asset management, or related disciplines. Hands-on experience with SQL, Python, R, or similar technologies for data extraction, analysis, and reporting. Experience developing dashboards and reports using Power BI, Tableau, Excel, or similar visualization tools. Strong analytical and problem-solving skills, including interpreting large datasets and identifying meaningful trends. Understanding of data validation, data quality, and reporting processes. Ability to translate business requirements into analytical outputs and actionable insights. Strong communication and cross-functional collaboration skills; ability to independently manage assigned work and meet timelines. Willingness to learn facility engineering, asset management, and maintenance processes in a global supply chain environment. Preferred Requirements Exposure to facility engineering, maintenance operations, asset management, or MHE in distribution or manufacturing environments. Exposure to retail operations, supply chain, distribution centers, warehouse operations, manufacturing, logistics, or industrial engineering environments. Familiarity with CMMS/EAM platforms such as SAP PM, IBM Maximo. Experience working with operational, equipment, or maintenance datasets. Exposure to reporting automation, predictive analytics, AI/ML, or advanced analytics. Exposure to working in warehouse operations Useful Links- Life at Target- https://india.target.com/ Benefits- https://india.target.com/life-at-target/workplace/benefits Know More About Us here: Life at Target : https://india.target.com/ Benefits : https://india.target.com/life-at-target/workplace/benefits Culture : https://india.target.com/life-at-target/belonging Target Tech : https://tech.target.com/