Data Engineer

Role overview

Responsibilities

• Conduct exploratory analysis of structured and unstructured datasets and translate business requirements into robust data solutions.
• Design, build, and optimize ETL and ELT pipelines integrating diverse sources with the Enterprise Data Warehouse and Snowflake Data Cloud.
• Develop dbt-based analytics-ready data models with modular design, automated testing, reusability, and maintainability.
• Design reusable semantic and data consumption layers for AI, agentic solutions, dashboards, reports, and conversational analytics.
• Use Snowflake Cortex to integrate AI and LLM capabilities into data pipelines.
• Enforce data quality, observability, lineage, governance, access control, compliance, CI/CD, and version control standards.
• Collaborate with architects, analysts, and business stakeholders on data strategy and scalable data solutions.

Minimum qualifications

• Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related technical field, or equivalent practical experience.
• At least 5 years of progressive data engineering experience in cloud data warehousing and modern data platforms.
• At least 2 years of hands-on experience developing AI and agentic solutions on Snowflake, AWS, or GCP.
• Deep Snowflake Data Cloud expertise, including architecture, security, and operational best practices.
• Strong dbt proficiency, including data modeling, automated testing, and CI/CD integration.
• Advanced SQL and practical Python skills for data manipulation and automation.
• At least 5 years of experience with leading BI or reporting tools such as Sigma or Power BI.

Preferred qualifications

• Experience with data quality, observability, and lineage tools.
• Familiarity with advanced Snowflake capabilities including zero-copy cloning, secure data sharing, external tables, Snowpark, dynamic tables, or MCP gateways.
• Understanding of data and solution architecture principles.
• Exposure to Tableau, ThoughtSpot, or other BI and reporting tools.

Ways of working

• Demonstrated experience applying Agile, Scrum, or Kanban methodologies in a data engineering environment.
• The role calls for self-directed delivery with minimal supervision.

About Cisco