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Mid-level generalist data role, known global brand, and 2–5 years experience increase candidate competition.
Medium — analytics and SQL skills transfer broadly but logistics domain knowledge adds moderate industry specificity.
High due to explicit 2–5 years requirement plus mandatory SQL/Python and logistics domain experience.
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Own availability and quality 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 actionable insights into logistics performance.
Partner with cross-functional teams to execute analytics demand, uphold data governance standards, and enhance reporting solutions for data-driven 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.
Experience with data visualization tools (Power BI, Tableau), data manipulation tools (SQL, Excel, Python), and logistics ERP systems.
Advanced English communication skills for effective interaction in a global, cross-functional environment.
Experience supporting analytics initiatives within logistics or end-to-end supply chain environments including transportation, fulfillment, and trade compliance.
Familiarity with data governance, KPI standardization, and data quality management in a global enterprise environment.
Comfortable working in a hybrid model with at least Monday, Tuesday, and Thursday onsite presence as per company policy.