Staff Analytics Engineer

As part of the Data team at Cribl, you will own the evolution of our analytics engineering platform, ensuring our data models are trusted, scalable, and AI-ready.

Analytics Engineering transforms raw data into governed, business-ready models that power analytics, executive reporting, and AI-enabled decision making. As Cribl continues to scale, this role will establish the architecture, standards, and technical practices that enable consistent, trusted analytics across Product, Engineering, Customer, Marketing, GTM, and Finance.

You will serve as a technical leader for analytics engineering, partnering closely with analysts, data engineers, governance, and business stakeholders to improve the quality, consistency, and reliability of our warehouse. While analysts own business logic within their domains, you will own the technical architecture, modeling standards, and engineering practices that allow our analytics platform to scale.

If you enjoy building systems that enable others, care deeply about data quality and developer experience, and want to shape the future of analytics at Cribl, we'd love to talk to you.

Own the long-term architecture and evolution of Cribl's analytics engineering platform, including foundational model stabilization and AI readiness.

Design, build, and maintain certified dbt models as the authoritative source for business-critical metrics.

Establish and enforce analytics engineering standards for modeling, testing, documentation, and code review, including review of high-impact dbt changes.

Design and maintain semantic and metadata layers that enable reliable AI-powered analytics and self-service.

Partner with analysts to migrate high-value business logic from Omni into governed warehouse models.

Partner with Data Engineering to improve source reliability, warehouse architecture, and Snowflake performance and cost efficiency.