Staff, Business Intelligence Engineer

Responsibilities

• Utilize advanced analytical techniques to analyze large datasets, extract meaningful insights, and provide actionable recommendations to enhance revenue operations efficiency.
• Develop and maintain automated data reconciliation and quality checks to proactively identify and resolve discrepancies, ensuring accuracy and consistency of critical reports and dashboards.
• Create compelling visualizations to effectively communicate complex data insights, making information accessible and actionable for a diverse audience.
• Build and maintain data models to support GTM, helping the organization make informed strategic decisions.
• Drive the automation of our business intelligence ecosystem by treating dashboards and semantic layers as code. Leverage Git, automated testing frameworks, and CI/CD pipelines to ensure our data infrastructure is reproducible, version-controlled, and highly scalable.
• Work closely with various teams, including Sales, Marketing, Finance, and Product, to understand business requirements and provide analytical support.
• Identify opportunities to enhance data quality, reporting processes, and analytics tools to drive continuous improvement in data analysis capabilities.

Requirements

• Minimum 8 years of professional experience in business intelligence, analytics engineering, data engineering, or a related discipline, with a preference for direct experience supporting GTM or sales analytics in a SaaS environment.
• Experience with business intelligence platforms such as Tableau, particularly in the context of executive reporting and sales analytics.
• Advanced expertise in SQL and hands-on experience designing data models.
• Demonstrated ability to partner with cross-functional stakeholders to codify, document, and reconcile critical business metrics, ensuring company-wide data alignment.
• Proven track record of implementing robust data quality and testing frameworks, including expertise with CI/CD and data observability.
• Strong technical communication and mentorship skills, with the ability to convey complex concepts to a range of audiences.

Nice-to-Haves

• Bachelor’s or Master’s degree in a quantitative discipline (e.g., Computer Science, Engineering, Mathematics, Economics).
• A software engineering mindset applied to data - understanding code reviews, automated testing, and environment separation (Dev/Staging/Prod).
• Experience with code-based BI and semantic tools to orchestrate data pipelines (e.g., Looker/LookML, dbt, Cube.js, or Apache Superset).
• Strong proficiency with Git version control and CI/CD tools (e.g., GitHub Actions, GitLab CI, Jenkins).
• Experience with AI products such as Claude, Cortex, Glean, Gemini.
• Experience with GTM technology stacks (e.g., Salesforce, Gong, etc).
• Experience evangelizing and establishing data culture and best practices within a fast-paced technology organization.