Global Logistics Data Analytics Analyst

Job description

Rockwell Automation is a global technology leader focused on helping the world’s manufacturers be more productive, sustainable, and agile. With more than 28,000 employees who make the world better every day, we know we have something special. Behind our customers - amazing companies that help feed the world, provide life-saving medicine on a global scale, and focus on clean water and green mobility - our people are energized problem solvers that take pride in how the work we do changes the world for the better. We welcome all makers, forward thinkers, and problem solvers who are looking for a place to do their best work. And if that’s you we would love to have you join us! Job Description Position Summary The Logistics Data Analytics Analyst is a key contributor within the Global Logistics Data Analytics team, driving the availability and quality of logistics data across regions. This role is responsible for transforming raw logistics data into actionable insights through the development of data pipelines, dashboards, reports, and analytical models. The position partners with cross-functional teams—including Analytics, Center of Excellence ( CoE ), Operations (fulfillment, transportation, trade compliance), and Performance—to deliver trusted “source of truth” metrics and insights, enabling timely and data-driven decision-making. A key expectation of this role is to execute analytics demand efficiently, uphold data quality standards, and continuously enhance reporting solutions to improve visibility and insight into logistics performance. Your Responsibilities: 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.