Staff Analytics Engineer

Remote (United States)

About the Role

An experienced Staff Analytics Engineer is needed to help build and scale a modern analytics infrastructure that powers data-driven decision-making across multiple business functions. This opportunity is focused on creating trusted analytics systems, improving data quality, enabling self-service reporting, and building AI-powered analytics solutions.

This role combines analytics engineering, data architecture, semantic modeling, and AI-enhanced analytics development within a fast-paced engineering organization.

Compensation: $86.54 - $105.77 per hour plus equity opportunities

What You'll Do

• Own and continuously improve a scalable analytics layer that supports company-wide business intelligence and reporting initiatives
• Design, build, and maintain well-structured datasets using dbt, SQL, Snowflake, and semantic layer technologies
• Transform raw operational data into reliable, trusted metrics used across Product, Finance, GTM, and Operations teams
• Partner closely with analysts, engineers, and business stakeholders to define key metrics and reporting standards
• Enable self-service analytics capabilities across departments
• Develop scalable semantic layers that provide consistent and reliable business definitions
• Implement data quality frameworks, validation systems, monitoring processes, and automated testing strategies
• Improve trust, consistency, and reliability across analytics datasets and reporting systems
• Build AI-powered analytics tools and intelligent data products
• Create systems capable of automating analytical workflows and generating business insights
• Contribute to AI-driven analytics agents that leverage semantic layers to answer business questions
• Drive scalable analytics architecture and support long-term platform evolution
• Collaborate cross-functionally with Product, Engineering, Finance, GTM, and Operations teams
• Lead high-impact analytics initiatives from planning through implementation and delivery
• Help establish best practices for scalable analytics engineering and modern data infrastructure

Qualifications

• 8+ years of experience in analytics engineering, data engineering, or related technical roles
• Strong background leading large-scale analytics or cross-functional data initiatives
• Advanced expertise with dbt, including large transformation layers and reusable data models
• Expert-level SQL skills
• Hands-on experience working with Snowflake or similar cloud-based data warehouses
• Experience building and managing scalable semantic layers
• Strong understanding of metric governance and analytics consistency
• Experience designing modular and scalable data architectures, including Kimball modeling or OBT methodologies
• Strong background in analytics testing frameworks, monitoring systems, and data validation strategies
• Experience building internal data products and analytics tooling
• Ability to partner effectively with both technical and non-technical stakeholders
• Strong communication skills with the ability to explain technical concepts and tradeoffs clearly
• Experience operating in fast-moving, high-growth environments
• Strong understanding of software architecture and scalable platform design principles
• Experience supporting multi-tenant platform environments
• Demonstrated success delivering analytics initiatives from concept to production
• Daily hands-on use of AI-assisted engineering workflows and AI productivity tools
• Strong understanding of how AI can improve analytics engineering, modeling, and decision-making processes
• Ability to work independently while driving technical leadership across teams

Preferred Qualifications

• Experience with Airflow orchestration workflows
• Experience working with Sigma and Hex analytics platforms
• Strong Python development experience
• Experience designing AI-enhanced analytics systems and automated insight generation workflows

Technology Stack

• Frontend Analytics Tools: Sigma, Hex
• Backend Technologies: dbt, SQL, Python
• Data Warehouse: Snowflake
• Infrastructure: Airflow

Work Environment

This is a fully remote opportunity available across the United States. The role is part of a fast-growing engineering organization focused on modern analytics systems, scalable data infrastructure, and AI-powered product development.