- Lead complex exploratory data analysis initiatives to identify strategic trends and patterns within structured and unstructured datasets, informing architectural decisions.
- Drive the translation of highly complex business requirements into strategic, scalable, and resilient data solutions, integrating insights from diverse non-ERP sources with our Enterprise Data Warehouse (EDW).
- Architect, design, and oversee the development and optimization of highly scalable ELT/ETL pipelines to ingest, transform, and publish data into the Snowflake Data Cloud, ensuring performance and reliability.
- Define standards for, and oversee the development and maintenance of, high-quality, analytics-ready data models using dbt, emphasizing modular design, reusability, rigorous testing, and CI/CD integration.
- Lead the design and implementation of a reusable semantic layer that adheres to enterprise architectural standards and supports diverse, high-volume consumption patterns (AI, agentic solutions, dashboards).
- Drive the integration of Snowflake Cortex and other AI/LLM capabilities directly into data pipelines, enabling advanced analytics and intelligent automation.
- Lead the design and development of advanced data consumption layers, including sophisticated dashboards, reports, conversational analytics, and agentic solutions.
- Applies working knowledge of databases, relational databases, cloud services, and scripting languages
- Contributes to data quality and compliance, including cleansing and scrubbing of data, data integrations and data quality framework
- Establish and champion best practices for data quality, observability, lineage, governance, and access control across our AI-ready data architecture, ensuring data trust and compliance.
- Serve as a technical liaison, collaborating strategically with data architects, analysts, and business stakeholders to define and execute long-term data strategies and roadmaps. Work in partnership and guidance from the core team at onsite
- Drive the establishment and continuous improvement of technical governance, CI/CD best practices, and rigorous version control standards to ensure the integrity, security, and scalability of our modern data stack.
- Experience with cloud-native services for data processing and orchestration (e.g., AWS Glue, Lambda, Step Functions, GCP Dataflow, Cloud Composer).
- Demonstrated experience applying Agile, Scrum, or Kanban methodologies within a data engineering environment.
- A self-starter with proven expertise to deliver outcomes with minimal supervision
- Provide technical guidance and mentorship to junior data engineers, fostering a culture of excellence and continuous learning.
- Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related technical field, or equivalent practical experience.
- 8+ years of progressive experience in data engineering, with a proven track record in architecting and leading cloud data warehousing and modern data platform implementations.
- 4+ years of experience leading or architecting AI and agentic solutions, specifically on platforms like Snowflake, AWS, or GCP.
- Expert-level proficiency and architectural leadership with the Snowflake Data Cloud, encompassing its advanced features, security model, and operational best practices.
- Expert-level proficiency and strategic application of dbt (Data Build Tool) for designing, developing, and maintaining complex data models, including automated testing and CI/CD integration.
- Mastery in SQL and Python, with a focus on scalable data processing, automation, and API integration.
- Extensive experience (7+ years) with leading BI/reporting tools such as Sigma or Power BI, with a deep understanding of data visualization best practices.
- Demonstrated expertise in implementing and managing data quality, observability, and lineage frameworks and tools across enterprise data pipelines.Deep architectural understanding and practical application of advanced Snowflake capabilities (e.g., zero-copy cloning, secure data sharing, external tables, Snowpark, dynamic tables, MCP gateways).Proven track record in defining and implementing enterprise-level data and solution architectures, including experience with data mesh or data fabric principles.Comprehensive understanding of the broader analytics ecosystem, including diverse BI/reporting tools (e.g., Tableau, ThoughtSpot) and complex downstream consumption patterns.Previous experience guiding technical teams and presenting complex technical concepts to senior leadership.Snowflake Gen AI certification preferred
Why Cisco?
At Cisco, we’re revolutionizing how data and infrastructure connect and protect organizations in the AI era – and beyond. We’ve been innovating fearlessly for 40 years to create solutions that power how humans and technology work together across the physical and digital worlds. These solutions provide customers with unparalleled security, visibility, and insights across the entire digital footprint.
Fueled by the depth and breadth of our technology, we experiment and create meaningful solutions. Add to that our worldwide network of doers and experts, and you’ll see that the opportunities to grow and build are limitless. We work as a team, collaborating with empathy to make really big things happen on a global scale. Because our solutions are everywhere, our impact is everywhere.
We are Cisco, and our power starts with you.
Disclaimer
To ensure that we hire the best talent in the right way, we follow a strict hiring process and recently, Cisco has been made aware of fraudulent recruiters claiming to be from the company. Please be advised that any communication from Cisco about careers will:
- be in direct response to an application you have submitted through the company career site
- begin with screening or an interview
- originate from a Cisco email address, and
- be conducted across email, phone, or WebEx
Cisco will never make a job offer without conducting an interview process or ask you for money in any way. If you have been requested to apply for a role or have received an offer from a site other than https://careers.cisco.com or cisco.wd5.myworkday.com, do not provide any personal identifying information, including your Aadhaar or other personal identifying number, birth certificate, banking information, driver's license, or passport.
If you are the target of a recruiting scam, consider filing a report with your local law enforcement authorities. Cisco bears no responsibility, and cannot be held liable, for any claims, damages, expenses, or other inconvenience resulting from or in any way connected to recruiting scams.
Skills Required
- Bachelor's degree in Computer Science, Engineering, Information Systems, a related technical field, or equivalent practical experience
- 8+ years of progressive experience in data engineering, including architecting and leading cloud data warehousing and modern data platform implementations
- 4+ years of experience leading or architecting AI and agentic solutions on platforms such as Snowflake, AWS, or GCP
- Expert-level proficiency with the Snowflake Data Cloud, including advanced features, security, and operational best practices
- Expert-level proficiency with dbt for complex data models, automated testing, and CI/CD integration
- Mastery of SQL and Python for scalable data processing, automation, and API integration
- 7+ years of experience with BI and reporting tools such as Sigma or Power BI
- Expertise implementing and managing data quality, observability, and lineage frameworks
- Advanced Snowflake capabilities including zero-copy cloning, secure data sharing, external tables, Snowpark, dynamic tables, and MCP gateways
- Experience defining and implementing enterprise data and solution architectures, including data mesh or data fabric principles
- Understanding of analytics ecosystems and BI tools such as Tableau and ThoughtSpot
- Experience guiding technical teams and presenting complex technical concepts to senior leadership
- Snowflake Gen AI certification
Cisco Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Cisco and has not been reviewed or approved by Cisco.
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Healthcare Strength — Health coverage is described as broad, with medical options including PPOs, high-deductible plans, and regional HMOs. Feedback suggests robust wellness and mental-health resources, with some locations offering on-site support and second medical opinions.
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Leave & Time Off Breadth — Time off is highlighted through paid holidays, paid time off, and additional recharge days such as “Days for Me,” with generous volunteer time also mentioned. Feedback suggests these programs help support rest, volunteering, and critical life events.
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Parental & Family Support — Parental and family support appears extensive, including paid child-bonding leave, family medical leave, and caregiving resources. Observations also point to family-planning assistance and adoption or surrogacy support in some regions.
Cisco Insights
What We Do
Cisco (NASDAQ: CSCO) enables people to make powerful connections--whether in business, education, philanthropy, or creativity. Cisco hardware, software, and service offerings are used to create the Internet solutions that make networks possible--providing easy access to information anywhere, at any time. Cisco was founded in 1984 by a small group of computer scientists from Stanford University. Since the company's inception, Cisco engineers have been leaders in the development of Internet Protocol (IP)-based networking technologies. Today, with more than 71,000 employees worldwide, this tradition of innovation continues with industry-leading products and solutions in the company's core development areas of routing and switching, as well as in advanced technologies such as home networking, IP telephony, optical networking, security, storage area networking, and wireless technology. In addition to its products, Cisco provides a broad range of service offerings, including technical support and advanced services. Cisco sells its products and services, both directly through its own sales force as well as through its channel partners, to large enterprises, commercial businesses, service providers, and consumers.
