Principal Supply Chain Data Engineer & Analytics Lead
Accountabilities Develop and maintain scalable supply chain data models, pipelines, and structures that support reporting, analytics, and decision-making across logistics, planning, inventory, warehousing, and fulfillment.
Extract, transform, validate, and integrate data from ERP, MRP, DRP, WMS, WCS, TMS, planning, finance, and other enterprise systems.
Build reliable analytical datasets that provide consistent and accessible information across supply chain functions.
Design and deliver dashboards, scorecards, visualization solutions, and management reports that translate complex operational data into clear insights and recommended actions.
Analyze large and fragmented datasets to identify trends, root causes, operational risks, improvement opportunities, and performance drivers.
Develop predictive analytics, simulations, optimization models, machine learning applications, and AI-enabled decision-support tools.
Support opportunity identification and value creation by quantifying potential savings, operational impacts, customer service implications, and commercial trade-offs.
Develop analytical solutions addressing network performance, warehouse productivity, transportation costs, inventory positioning, demand and supply variability, and service performance.
Translate technical findings into executive-ready insights, business cases, recommendations, and transformation decision-support materials.
Partner with IT and data architecture teams to improve data accessibility, governance, automation, scalability, and long-term sustainability.
Identify opportunities to simplify, standardize, automate, and scale supply chain analytics and reporting processes.
Connect operational performance metrics with financial and commercial outcomes, including cost, margin, service, productivity, inventory, and working capital.
Document business requirements, data logic, metric definitions, assumptions, and analytical outputs to ensure solutions are repeatable and scalable.
Collaborate across supply chain, finance, technology, and other functions to deliver high-quality analytics and support transformation initiatives.
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 transform large and complex operational datasets into actionable insights, decision-support tools, and executable recommendations.
Experience extracting, transforming, validating, and analyzing data from ERP platforms and other supply chain systems.
Strong understanding of end-to-end supply chain processes, including demand planning, supply planning, MRP, DRP, warehousing, distribution, transportation, inventory, and customer fulfillment.
Advanced proficiency with SQL, Python, R, Alteryx, Power Query, or comparable data extraction, transformation, and analytics technologies.
Strong experience developing dashboards and visualization solutions using Power BI, Tableau, Qlik, or similar business intelligence platforms.
Knowledge of ERP and supply chain data structures, including master data, transactions, inventory, orders, production, procurement, warehousing, and logistics information.
Experience developing predictive models, forecasting tools, optimization models, simulation analyses, machine learning applications, or AI-enabled decision-support solutions.
Strong data quality, governance, validation, analytical modeling, and data storytelling capabilities.
Ability to connect operational analysis with financial and commercial implications, including cost, margin, service, inventory, productivity, and working capital.
Strong quantitative, analytical, and problem-solving skills with the ability to support complex operational and commercial decisions.
Excellent communication skills and the ability to explain complex data, models, assumptions, and recommendations to technical and non-technical stakeholders.
Ability to collaborate effectively across multiple functions and influence stakeholders toward data-driven decisions.
Strong organizational skills with the ability to manage competing priorities, work through ambiguity, and deliver high-quality solutions in a fast-paced transformation environment.
Experience with consulting, internal consulting, transformation offices, supply chain excellence teams, or advanced analytics organizations is preferred.
Experience in medical device, pharmaceutical, healthcare, consumer health, manufacturing, or another regulated supply chain environment is advantageous.
Familiarity with SAP, Oracle, Kinaxis, Blue Yonder, Manhattan, HighJump/Korber, SAP EWM, Dematic, or comparable ERP, planning, WMS, WCS, or supply chain execution platforms is preferred.
Lean Six Sigma, APICS CPIM/CSCP, project management, data engineering, data analytics, or AI/ML certifications or advanced training are a plus.
Must be authorized to work for any U.S. employer without requiring employment visa sponsorship.
Benefits
Starting salary range of $145,000–$165,000, depending on qualifications, experience, and other relevant factors.
Eligibility for short-term and/or long-term incentive compensation.
Medical, dental, and vision insurance.
Disability and life insurance coverage.
401(k) retirement plan with company match.
Tuition reimbursement for select degree programs.
Company holidays, floating holidays, paid vacation, and sick time.
Well-being and employee support benefits.
Opportunity to work remotely within the United States.
Opportunity to influence large-scale supply chain transformation through data, analytics, and AI.
Exposure to complex, cross-functional business challenges spanning planning, logistics, inventory, warehousing, and fulfillment.
Opportunity to develop and scale advanced analytics capabilities with significant business impact.
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