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Remote role, popular data analyst title, and broad Tableau/SQL/Python requirements increase competition.
Core analytics skills (SQL, Tableau, Python) are readily transferable across industries.
Explicit 2–4 year requirement plus mandatory Tableau, SQL, and data tooling makes screening relatively strict.
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Own operational data quality and reporting for global logistics systems by cleansing data, mapping data flows, and maintaining data integrity.
Develop and maintain dynamic dashboards and reports using Tableau, SQL, Excel, and internal tools to support leadership decision-making.
Implement controls to monitor and mitigate data quality risks and troubleshoot dashboard performance issues.
2-4 years experience in operational data analytics and visualization.
Proficiency in Tableau (Desktop, Server, Prep), MS Excel, and SQL (Oracle, Hive, MySQL).
Bachelor's degree in Computer Science, Statistics, Mathematics, Engineering, Business, or related field.
Familiarity with Python, R, or SAS for data analysis and automation.
Experienced operational data analyst with strong expertise in logistics or supply chain data environments.
Hands-on skills in developing and optimizing Tableau dashboards and automation workflows (Tableau Prep Flows, SSIS, Python scripts).
Capable of independent problem-solving and managing cross-functional stakeholder communications for reporting and data quality improvements.