Analytics Engineer

Role Description

We are hiring our first dedicated Analytics Engineer to help build and scale the data and AI foundation of our enterprise SaaS business. Reporting to the Sr. Director of AI & Analytics within our centralized Operations organization, this is a highly hands-on role focused on architecting scalable analytics systems and AI-enabled workflows that power decision-making across the company. This is a foundational hire with high ownership and long-term growth potential.

What You'll Do

• Enterprise Data Modeling & Architecture
  • Design and maintain scalable dbt data models in Snowflake that serve as trusted sources of truth across the business
  • Architect data pipelines and transformation workflows using Fivetran and modern ELT practices
  • Develop durable, extensible data assets that evolve as the company scales
  • Establish modeling standards, documentation practices, and governance frameworks
  • Partner with RevOps and Finance to define and operationalize core SaaS metrics (ARR, retention, expansion, pipeline, etc.)
• AI-Enabled Systems & Workflow Integration
  • Build data foundations that power internal AI applications and LLM-enabled workflows
  • Prototype and productionize AI-driven operational use cases
  • Integrate analytics and AI into everyday workflows using tools such as Notion, Cursor, Glean, and other emerging platforms
  • Design systems that embed data directly into operational processes — not just dashboards
• Cross-Functional Analytics Infrastructure
  • Partner with leaders across Sales, CS, Marketing, Finance, Product, and Engineering to translate business needs into scalable technical systems
  • Create reusable data assets that enable activation via Hightouch and analysis via Omni
  • Ensure architecture is scalable, secure, and adaptable to evolving enterprise requirements

Our Stack

• Analytics: Fivetran, dbt, Snowflake, Hightouch, Omni
• AI & Knowledge Systems: Notion, Cursor, Glean

Qualifications

• 3–6+ years of experience in analytics engineering, data engineering, or similar hands-on roles
• Strong SQL skills and deep understanding of modern data modeling (dimensional modeling, transformations, data contracts, etc.)
• Experience building in cloud data warehouses (Snowflake, BigQuery, Redshift, etc.)
• Comfort working in a fast-moving, evolving AI tooling landscape
• Systems-level thinker who designs for scalability, extensibility, and flexibility
• Naturally curious and energized by solving ambiguous problems
• Pride in building clean, durable architecture — not just shipping quick fixes
• Strong communication skills and ability to collaborate across business and technical teams

Benefits

• Competitive Salary
• Medical, Vision & Dental Benefits
• 401k
• Stock Options
• HSA Contribution
• Learning Stipend
• Flexible PTO Policy
• Quarterly company ME (mental escape) days
• Generous Parental Leave policy
• Home Office Stipend
• Mobile Phone Reimbursement
• Home Internet Reimbursement for Remote Employees
• Anniversary & Milestone Celebrations