Principal Supply Chain Data Engineer & Analytics Lead Job Details | Bausch+Lomb Companies Inc.

Bausch + Lomb is hiring a Principal Supply Chain Data Engineer and Analytics Lead to build the data foundation, analytics capabilities, and insight-generation tools supporting its supply chain transformation. The role develops data pipelines, dashboards, predictive analytics, and decision-support tools to improve supply chain performance and enable business decisions.

Responsibilities:

• Develop and maintain supply chain data models, pipelines, and data structures that enable consistent reporting, analytics, and decision support across logistics, planning, inventory, warehousing, and fulfillment processes
• Extract, transform, and integrate data from ERP, MRP, DRP, WMS, WCS, TMS, planning, finance, and other enterprise systems to create reliable analytical data sets
• Design and deliver dashboards, scorecards, visualization tools, and management reporting that translate complex data into clear business insights and recommended actions
• Analyze large, complex, and often fragmented data sets to identify patterns, root causes, risks, opportunities, and improvement levers across the end-to-end supply chain
• Develop predictive analytics, simulation tools, optimization models, and AI-enabled use cases that support service, cost, quality, inventory, and capacity decision-making
• Support opportunity funnel development by quantifying savings opportunities, operational impacts, customer service implications, and commercial trade-offs
• Create analytical tools that support decisions related to network performance, warehouse productivity, transportation cost, inventory positioning, demand and supply variability, and service performance
• Translate technical analysis into executive-ready insights, business cases, and recommendations that support transformation governance and leadership decision-making
• Collaborate with IT and data architecture teams to improve data accessibility, governance, automation, scalability, and long-term sustainability of analytics solutions
• Contribute to continuous improvement by identifying opportunities to simplify, standardize, automate, and scale supply chain analytics and reporting processes

Requirements:

• Bachelor's degree in supply chain management, Engineering, Data Science, Computer Science, Information Systems, Business Analytics, Operations Research, Finance, or a related discipline
• 5+ years of progressive experience in supply chain analytics, data engineering, business intelligence, operations analytics, consulting, or a related field
• Demonstrated ability to work with complex operational data and convert large data sets into business insights, decision-support tools, and executable recommendations
• Experience extracting, transforming, validating, and analyzing data from ERP systems and other supply chain platforms
• Strong understanding of end-to-end supply chain processes, including demand planning, supply planning, MRP, DRP, warehousing, distribution, transportation, inventory, and customer fulfillment
• Strong analytical, quantitative, and problem-solving skills with the ability to conduct commercial and operational decision-making analysis
• Ability to partner effectively with various functions
• Strong communication skills with the ability to explain complex data, models, assumptions, and insights to technical and non-technical audiences
• Ability to manage multiple priorities, work through ambiguity, and deliver high-quality analytics in a fast-paced transformation environment
• Advanced capability with SQL, Python, R, Alteryx, Power Query, or similar data extraction, transformation, and analytics tools
• Strong visualization and dashboard development experience using Power BI, Tableau, Qlik, or comparable business intelligence platforms
• Knowledge of ERP systems and supply chain data structures, including master data, transactions, inventory, orders, production, procurement, warehousing, and logistics data
• Experience building predictive models, forecasting tools, optimization models, simulation analyses, machine learning use cases, or AI-enabled decision-support solutions
• Ability to connect operational performance metrics with financial and commercial implications, including cost, margin, service, inventory, productivity, and working capital impacts
• Strong data quality, data governance, data validation, and data storytelling capabilities
• Experience documenting business requirements, data logic, metric definitions, assumptions, and model outputs for repeatable use across stakeholders
• Applicants must be authorized to work for ANY employer in the U.S. We are unable to sponsor or take over sponsorship of an employment Visa at this time
• Familiarity with Lean Six Sigma, structured problem solving, process mapping, or consulting-style analytics frameworks preferred
• Experience with a consulting firm, internal consulting group, transformation office, supply chain excellence team, or advanced analytics organization
• Experience in medical device, pharmaceutical, healthcare, consumer health, manufacturing, or other regulated supply chain environments
• Experience supporting logistics transformation, warehouse optimization, inventory analytics, planning improvement, network analysis, or service-cost-quality improvement initiatives
• Working knowledge of SAP, Oracle, Kinaxis, Blue Yonder, Manhattan, HighJump/Korber, SAP EWM, Dematic, or other ERP, planning, WMS, WCS, or supply chain execution platforms
• Certification or advanced training in data analytics, data engineering, supply chain management, Lean Six Sigma, APICS CPIM/CSCP, project management, or AI/ML preferred