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Mid-level data analytics role, metro location, broad skillset and known global brand increases candidate competition.
Technical analytics skills are transferable but logistics domain knowledge makes fit moderately sensitive across industries.
Explicit 2–5 year requirement plus logistics domain experience and mandatory SQL/PowerBI/Python skills raises shortlisting strictness.
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Own the quality and availability of global logistics data by validating, cleansing, and monitoring datasets within the enterprise data lake.
Develop and maintain dashboards, reports, and analytical models to provide visibility and insights into logistics performance (service, cost, compliance, productivity).
Partner cross-functionally to translate business needs into scalable analytics solutions and deliver trusted metrics for data-driven logistics decision-making.
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.
Proficiency with data visualization tools (e.g., Power BI, Tableau) and data manipulation tools (e.g., SQL, Excel, Python), plus exposure to logistics ERP systems.
Ability to work in a global, cross-functional environment with advanced English communication skills.
Experience supporting analytics initiatives within logistics or end-to-end supply chain functions, including transportation, fulfillment, or trade compliance.
Familiarity with global data governance, KPI standardization, and data quality management practices.
Comfortable working in hybrid mode at Rockwell locations on specified days with experience in enterprise data platforms (data lakes, Databricks) and logistics systems (SAP, TMS, WMS).