Data Analysis Manager

Meet the Team

The Supply Chain Transformation team is driving Cisco's digital evolution across Costing, Strategic Sourcing, and Supplier Management. We partner with business, engineering, finance, supply chain, and suppliers to modernize decision-making through AI, automation, advanced analytics, and scalable data products.

Our mission is to improve cost competitiveness, strengthen supplier performance, and enable faster, smarter sourcing decisions by combining deep supply chain expertise with modern data, AI, and decision intelligence.

Your Impact

As a Data Analysis Manager, you will build data products, analytical solutions, and intelligent workflows that shape sourcing, costing, and supplier management decisions across Cisco's global supply chain. Leveraging Python, APIs, AI, automation, and modern cloud data platforms, you will transform complex data into actionable insights that improve operational and financial outcomes.

This is a hands-on technical leadership role. You will design and deliver scalable solutions, mentor engineers and analysts, establish engineering best practices, and help accelerate the team's adoption of AI-assisted development, intelligent automation, and modern analytics.

Responsibilities

Design and deliver data products, analytics, automation, and AI-enabled solutions that support costing, strategic sourcing, supplier management, and procurement transformation.

Analyze large-scale supply chain, supplier, pricing, spend, manufacturing, and engineering data to identify opportunities for cost optimization, operational efficiency, and risk mitigation.

Build scalable data pipelines, API integrations, AI agents, and intelligent workflows that provide trusted, reusable, and self-service business insights.

Leverage modern software engineering practices and AI-assisted development tools to rapidly prototype, build, and enhance analytical solutions while maintaining high standards for quality, security, and maintainability.

Partner with sourcing, supplier management, finance, engineering, and business leaders to translate complex business challenges into scalable, data-driven solutions and decision intelligence.

Lead technical solution design, perform code reviews, mentor team members, and champion best practices across analytics, data engineering, AI, and software development.

Minimum Qualifications

• Bachelor's degree in Supply Chain, Engineering, Computer Science, Data Science, Mathematics, Statistics, or a related technical discipline.
• 7+ years of experience in data analytics, supply chain analytics, procurement analytics, business analytics, or related technical disciplines.
• 5+ years of hands-on Python development for data engineering, analytics, automation, and software solution development.
• Experience developing and integrating REST APIs, event-driven services, and enterprise data solutions.
• Strong understanding of data modeling, business logic, and analytical techniques for structured, semi-structured, and unstructured data.
• Experience building scalable cloud-native solutions using containerization technologies such as Docker and Kubernetes, with knowledge of modern deployment frameworks and CI/CD practices.
• Experience working with supply chain, sourcing, procurement, costing, supplier, manufacturing, engineering, or financial datasets.
  
  

Preferred Qualifications

• Experience with AI/LLMs, agentic AI, Model Context Protocol (MCP), retrieval-augmented generation (RAG), or AI-enabled enterprise applications.
• Strong understanding of end-to-end data architecture, including data ingestion, curation, transformation, orchestration, deployment, and visualization.
• Experience with modern cloud data platforms and data engineering ecosystems such as Snowflake, Databricks, Azure, AWS, or GCP.
• Experience with data visualization and business intelligence platforms such as Tableau, Power BI, Looker, or similar tools.
• Experience supporting strategic sourcing, supplier performance, should-cost modeling, supplier risk management, or procurement transformation initiatives.
• Demonstrated ability to mentor technical teams and establish best practices across analytics, data engineering, AI, and software engineering.
• Strong communication and stakeholder management skills with the ability to translate complex analytical findings into actionable business decisions.
• Experience designing and delivering reusable data products, semantic data models, or enterprise analytics platforms that enable self-service decision intelligence across business functions.
• Experience using AI coding assistants (e.g., GitHub Copilot, Cursor, Claude Code, or similar)
  
  

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