Data Engineer

As a Data Engineer with an AI Analytics specialization, you will own the design and delivery of AI-augmented data pipelines and analytical systems within the CIA with Data and Analytics organization. You will build the data infrastructure that feeds machine learning models and LLM-based insight pipelines, develop analytical frameworks that surface AI-generated insights to business stakeholders, and contribute to the architectural evolution of Cisco’s customer analytics AI platform. This role requires both data engineering depth and genuine AI curiosity.

• Design and build data pipelines in Snowflake and Python that serve as the structured data layer for LLM-based insight generation—including the Dynamic NPS Forecast AI Summary pipeline and similar AI-augmented workflows.
• Develop and maintain dbt models that produce clean, well-tested, AI-ready data surfaces—including feature engineering tables, aggregation layers, and prompt-context data structures for generative AI use cases.
• Write production-grade Python for data ingestion, API payload processing, LLM API integration, prompt construction, response parsing, and structured output storage.
• Integrate with GCP services (Cloud Run, API Gateway, Vertex AI) and Cisco AI tooling to build end-to-end AI data pipelines from raw customer signals to executive-ready insight delivery.
• Build and instrument data quality and observability frameworks that prevent AI pipeline failures from propagating incorrect or hallucinated insights to downstream business consumers.
• Collaborate with BI engineers on analytical output surfaces—ensuring AI-generated insights are structured for clean consumption in Power BI or other visualization layers.
  • Stay at the frontier of AI-native data tooling—Snowflake Cortex, dbt Copilot, LangChain, vector databases, embedding pipelines—and bring forward-looking technical judgment to the team’s architectural decisions.