Data Engineer
On-siteBengaluru, Karnataka, India
Job Summary
Data Engineer with an AI Analytics specialization who will own the design and delivery of AI-augmented data pipelines and analytical systems within Cisco’s CIA with Data and Analytics organization. Build the data infrastructure that feeds machine learning models and LLM-based insight pipelines, develop analytical frameworks to surface AI-generated insights to business stakeholders, and contribute to the architectural evolution of Cisco’s customer analytics AI platform. Design and build data pipelines in Snowflake and Python for LLM-based insight generation, develop and maintain dbt models, write production-grade Python for data ingestion and LLM interaction, integrate with GCP services (Cloud Run, API Gateway, Vertex AI) and Cisco AI tooling, and establish data quality and observability frameworks while collaborating with BI engineers to ensure AI outputs are consumable in visualization layers. Stay at the frontier of AI-native data tooling and apply forward-looking architectural judgment to the team’s decisions.
Required Qualifications
- 4+ years of professional experience in data engineering, analytics engineering, or a closely related role, with demonstrated production ownership of Snowflake environments including schema design, query optimization, and data pipeline reliability
- Intermediate to advanced Python proficiency for data engineering tasks: API integration, JSON payload processing, LLM API calls (OpenAI, Anthropic, or equivalent), structured output parsing, and pipeline automation using pandas, requests, and related libraries
- Expert-level SQL with demonstrated ability to write complex aggregations, window functions, and multi-level hierarchical queries in a Snowflake environment—including performance profiling and optimization
- Working proficiency in dbt: authoring of incremental models, Jinja macros, test frameworks, and snapshot strategies, with demonstrated understanding of how dbt model quality directly affects downstream analytical and AI pipeline reliability
- Demonstrated experience building or contributing to at least one AI-augmented data pipeline: consuming LLM API responses as structured data, building feature tables for ML models, or constructing prompt-context data layers for generative AI workflows
Hiring someone like this?
Get your role in front of qualified candidates on Sorce.