01Responsibilities
Ensure the availability and quality of logistics data by validating, cleansing, and monitoring datasets integrated into the enterprise data lake.Develop, maintain, and enhance dashboards, reports, and scorecards that provide visibility into logistics performance (service, cost, compliance, productivity).Translate business requirements into scalable data models and analytical solutions in partnership with the ISC Data Analytics team.Perform data analysis to identify trends, root causes, and opportunities, enabling operational and strategic decision-making.Ensure alignment with global KPI definitions, data standards, and governance frameworks established by analytics leadership.Execute intake and prioritization of analytics demand by documenting requirements and delivering solutions within agreed timelines.Partner with cross-functional teams (Operations, CoE, Performance, GPO) to deliver analytics solutions aligned with logistics priorities.Continuously improve data visualization, reporting efficiency, and storytelling techniques to drive user adoption and business impact.The Essentials - You Will Have:Bachelor's degree in Supply Chain, Logistics, Industrial Engineering, Computer Science, Data/Analytics, Statistics, Business, or related field.2-5 years of experience in logistics, transportation, supply chain, or data analytics.Experience working with data visualization tools (e.g., Power BI, Tableau), data manipulation tools (e.g., SQL, Excel, Python), and logistics ERP systems.Advanced English communication skills (written and verbal), with the ability to effectively interact in a global, cross-functional environment.Strong technical ability to develop analytics solutions, combined with the capability to understand and translate end-to-end logistics processes and business requirements into actionable outcomes.The Preferred - You Might Also Have:Experience supporting analytics initiatives within logistics or end-to-end supply chain environments (transportation, fulfillment, trade compliance).Familiarity with data governance practices, KPI standardization, and data quality management in a global environment.Experience working with enterprise data platforms and systems (e.g., data lakes, Databricks, SAP, TMS, WMS).Ability to communicate analytical insights effectively through data storytelling, influencing stakeholders and driving business impact.Experience with data pipeline development or dataflows in enterprise analytics environments.Rockwell Automation's hybrid policy aligns that employees are expected to work at a Rockwell location at least Mondays, Tuesdays, and Thursdays unless they have a business obligation out of the office. .
