Data Engineer

Overview

Data Engineer on Cisco's Commerce Intelligence Data & Analytics team, building a scalable, unified, AI-ready data foundation that supports business decisions and automated actions.

What you'll do

• Conduct in-depth exploratory data analysis to uncover trends and patterns in structured and unstructured datasets.
• Translate complex business requirements into robust data solutions, integrating insights from diverse non-ERP sources with the Enterprise Data Warehouse (EDW).
• Design, build, and optimize scalable ELT/ETL pipelines to ingest, transform, and publish data into the Snowflake Data Cloud.
• Develop and maintain high-quality, analytics-ready data models using dbt, emphasizing modular design, reusability, rigorous testing, and maintainability.
• Design and implement a reusable semantic layer that adheres to architectural standards and supports various consumption patterns (AI, agentic solutions, dashboards).
• Leverage Snowflake Cortex to integrate AI/LLM capabilities directly into data pipelines, enabling advanced analytics.
• Design and develop data consumption layers, including dashboards, reports, conversational analytics, and agentic solutions.
• Champion and enforce data quality, observability, lineage, governance, and access control standards across the AI-ready data architecture.
• Apply working knowledge of databases, relational databases, cloud services, and scripting languages.
• Contribute to data quality and compliance, including cleansing and scrubbing of data, data integrations, and the data quality framework.
• Collaborate strategically with data architects, analysts, and business stakeholders to define long-term data strategies and deliver scalable, reliable data solutions.
• Establish and enforce technical governance, CI/CD best practices, and rigorous version control to ensure integrity, security, and scalability of the modern data stack.
• Apply Agile, Scrum, or Kanban methodologies within a data engineering environment.
• Deliver outcomes with minimal supervision.

What you'll need

• Bachelor's degree in Computer Science, Engineering, Information Systems, or a related technical field, or equivalent practical experience.
• 5+ years of progressive experience in data engineering, with a proven track record in cloud data warehousing and modern data platform implementations.
• 2+ years of hands-on experience developing AI and agentic solutions, specifically on platforms like Snowflake, AWS, or GCP.
• Deep expertise with the Snowflake Data Cloud, including its architecture, security model, and operational best practices.
• Strong proficiency with dbt (Data Build Tool) for designing, developing, and maintaining data models, including automated testing and CI/CD integration.
• Advanced SQL skills and practical working knowledge of Python for data manipulation and automation.
• 5+ years of experience with leading BI/reporting tools such as Sigma or Power BI.

Nice to have

• Experience with data quality, observability, and lineage tools to enhance monitoring, validation, and governance across complex data pipelines.
• Familiarity with advanced Snowflake capabilities (e.g., zero-copy cloning, secure data sharing, external tables, Snowpark, dynamic tables, MCP gateways).
• Solid understanding of data and solution architecture principles.
• Exposure to other BI/reporting tools (e.g., Tableau, ThoughtSpot) and a keen understanding of diverse downstream analytics consumption patterns.

Details

• Location: Bangalore, India.
• Work with the extended team across US time zones.
• Collaborate with business functions across various time zones.