serverobotics - Data Analyst, Supply Chain
Requirements
• Required Experience, Qualifications, and Skills • 5 years of hands-on experience in data analysis, data engineering, workflow automation, or similar technical roles. • Strong general knowledge of data structures and data management, both for big data using cloud databases and small data using excel & google sheets. • Advanced knowledge of SQL and at least one other programming language (ideally Python or Javascript). • Proficiency in modern AI-driven development including AI coding tools (e.g., Claude Code, GitHub Copilot, Codex), Model Context Protocol (MCP), configuration of Skills, sub-agents, etc. and familiarity with popular AI orchestration frameworks such as Langgraph, OpenAI API/SDK, Gemini API/SDK, etc. • Experience designing data models and transforming data from multiple operational systems into clean, reliable datasets for reporting and analysis. • Strong analytical and problem solving skills, with the ability to translate complex data into actionable business recommendations for nontechnical stakeholders. • Demonstrated ability to independently manage multiple projects, prioritize competing requests, and deliver high quality work in a fast paced environment. • Preferred Experience, Qualifications, and Skills • Google Cloud Platform (GCP): Specifically Cloud Run, BigQuery, and other supporting services. • Google Workspace / G Suite: Specifically Google Sheets and Google Apps Script. • NetSuite: Specifically working with the NetSuite API. • Supply Chain Tech Experience: Applying these data and technology skills specifically within supply chain, logistics, or e-commerce operations. • Experience working with third party logistics (3PL), fulfillment, inventory management, or transportation management systems. • Familiarity with data observability, monitoring, and data quality frameworks in production environments.
Responsibilities
• Develop and manage API-based workflows to ensure seamless communication between our core business platforms and external logistics partners. • Design, build, and maintain automated pipelines to retrieve and route data across various internal and external databases and tools. • Perform hands-on data analysis (e.g., tracking average shipping times, inventory flows, etc.) and build automated spreadsheets and/or dashboards for stakeholders. • Implement error handling, alerting, etc. to ensure data workflows run consistently and accurately. • Partner with Supply Chain, Operations, Finance, and Engineering stakeholders to define KPIs, reporting requirements, and data quality standards across supply chain processes. • Conduct root cause analysis on operational issues and recommend process improvements that reduce cost, improve inventory accuracy, and increase logistics performance. • Create and maintain technical documentation for data models, integrations, workflows, and reporting systems to support long term scalability and knowledge sharing.
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