Senior Data & Analytics Platform Engineer (Snowflake)

TL;DR

Senior Data & Analytics Platform Engineer (Snowflake): Designing and building the enterprise data platform that powers analytics and AI with an accent on dbt pipelines, semantic modeling, and Snowflake architecture. Focus on creating AI-ready datasets, optimizing platform performance, and delivering high-impact data products for C-suite stakeholders.

Location: Must be based in the United States

Salary: $105,000 – $165,000

Company

A leading global analytics software company helping businesses in over 100 countries make better decisions through AI and big data.

What you will do

• Design, build, and own the end-to-end lifecycle of analytics data products from ingestion to semantic models.
• Develop and maintain dbt models, tests, and CI/CD pipelines for enterprise BI use cases.
• Build semantic models that enable AI agents and BI tools to consume data without requiring SQL.
• Manage Snowflake platform architecture, including RBAC, query optimization, and cost management.
• Partner with cross-department stakeholders to translate business needs into scalable data solutions.
• Contribute to the AI-powered analytics platform by building data foundations for Cortex Agents.

Requirements

• Must be based in the United States
• Extensive experience with Snowflake data modeling, architecture, and administration.
• Strong proficiency in dbt, including models, tests, macros, and CI/CD pipelines.
• Solid understanding of dimensional modeling, star schemas, and semantic layer design.
• Experience with Fivetran and ELT data integration patterns.
• Strong SQL skills and experience with modern BI/visualization tools.

Nice to have

• Experience with Python and Terraform.
• Familiarity with AI/LLM concepts like Snowflake Cortex and semantic agents.
• Experience with GitHub Actions or similar CI/CD systems.
• Background in DataOps or workflow automation tools.

Culture & Benefits

• Inclusive culture focused on ownership, customer delight, and mutual respect.
• Competitive compensation and rewards programs.
• Commitment to work-life balance and professional development.
• Access to employee resource groups and diverse social events.
• Opportunity to work on high-impact, AI-driven enterprise analytics products.