Data Analysis Manager- 7+ years of experience in data analytics, business intelligence, operations analytics, supply chain analytics, or related technical disciplines.
Cisco · Posted Sep 30
Networking, cloud, cybersecurity, and enterprise IT infrastructure services
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About the role
The Global Process and Business Intelligence group is a core component of the Product Operations Central team, providing centralized multi-disciplinary expertise that strengthens the strategic and operational framework for Business Units across Cisco's product portfolio. The team defines data quality standards and delivers business intelligence and data visualization supporting product lifecycle management, New Product Introduction, sustaining, and end-to-end supply chain processes. This hands-on technical leadership role builds trusted data products, BI solutions, and intelligent workflows using Python, SQL, APIs, AI, automation, and modern cloud data platforms, while mentoring engineers and analysts and establishing engineering and data quality best practices.
What you will do
- Own data quality — Define and enforce data quality standards, including accuracy, completeness, timeliness, and consistency, for product lifecycle, NPI, sustaining, and supply chain data, and make data issues visible to the owners who can fix them.
- Deliver business intelligence — Design and deliver dashboards, data products, and AI-enabled solutions that give BU and Product Operations leaders a clear view of product lifecycle health, NPI readiness, sustaining performance, and end-to-end supply chain execution.
- Analyze at scale. - Analyze large-scale product, engineering, operations, and supply chain datasets to find risks, bottlenecks, and opportunities to improve operational efficiency across Cisco’s product portfolio.
- Automate and engineer — Build scalable data pipelines, API integrations, AI agents, and intelligent workflows that replace manual reporting with trusted, reusable, self-service insights.
- Build with modern practices — Use modern software engineering practices and AI-assisted development tools to rapidly prototype, build, and improve analytical solutions while maintaining high standards for quality, security, and maintainability.
- Partner with the business — Partner with BU leaders, Product Operations, engineering, program management, and supply chain teams to understand the decisions they need to make and translate them into data-driven solutions. Challenge requirements when needed to make sure every deliverable drives a clear business outcome.
- Standardize globally — Standardize global processes, metric definitions, and reporting across BUs so leaders work from one consistent version of the truth.
- Lead and mentor — Lead technical solution design, perform code reviews, mentor team members, and champion best practices across analytics, BI, data engineering, AI, and software development.
Skills used in this role
What the employer is looking for
- Bachelor’s degree in engineering, Computer Science, Data Science, Mathematics, Statistics, Supply Chain, or a related technical discipline.
- 7+ years of experience in data analytics, business intelligence, operations analytics, supply chain analytics, or related technical disciplines.
- 5+ years of hands-on Python development for data engineering, analytics, automation, and software solution development.
- Experience with data visualization and business intelligence platforms such as Tableau, Power BI, Looker, or similar tools.
- Experience defining and implementing data quality rules, validation, and monitoring for enterprise datasets.
- 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 product lifecycle, engineering, manufacturing, operations, supply chain, 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 supporting product lifecycle management (PLM), NPI, sustaining engineering, product operations, or end-to-end supply chain initiatives.
- Experience with data governance, master data management, or metric standardization across multiple business units.
- Demonstrated ability to mentor technical teams and establish best practices across analytics, BI, data engineering, AI, and software engineering.
- Strong communication and stakeholder management skills with the ability to translate complex analytical findings into actionable business decisions for directors and executives.
- 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)
Benefits and support
- Compensation and benefits are detailed in the job posting
About Cisco
Cisco Systems, Inc. is a worldwide leader in IT, networking, and cybersecurity solutions that transform how people connect, communicate, and collaborate. The company specializes in routing, switching, data center infrastructure, and software-defined networking designed for enterprises of all sizes. Today, Cisco drives major advancements in AI infrastructure, observability, and secure hybrid work platforms.
- Industry
- Networking
- Company size
- 90000+ employees
- Founded
- 1984
- Location
- San Jose, California, USA
- Funding stage
- Public Company
Leadership
Chair and Chief Executive Officer
President and Chief Product Officer
Executive Vice President and Chief Financial Officer
Executive Vice President and Chief People, Policy & Purpose Officer
Executive Vice President and Chief Customer Experience Officer
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