Twilio
Senior
Build Twilio's trusted GTM business data layer in dbt and drive company-wide metric alignment
Twilio is hiring a Staff Analytics Engineer to design and maintain a formal business data layer in dbt that centralizes and reconciles GTM (sales/finance) data as a single source of truth, requiring at least 8 years of analytics/data engineering experience. The role is heavy on cross-functional metric definition with GTM Operations and Finance, automated data quality/reconciliation, and mentoring the broader data science and analytics team. Interview should probe dbt-based data modeling depth, data quality/testing frameworks, root-cause investigation of data anomalies, and the influence/communication skill needed to codify metrics org-wide.
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What this interview tests
- dbt-based business/semantic data layer design
- Cross-functional metric definition and reconciliation (Sales, Finance, GTM Ops)
- Automated data quality, reconciliation checks, dbt tests, CI/CD
- Root cause analysis of data anomalies and clear communication of findings
- Mentorship and enforcement of data modeling/testing best practices
Common question themes
Design a dbt data layer reconciling GTM data from multiple source systems
Walk through a time you root-caused a critical metric discrepancy
How do you drive alignment on a business metric definition across Sales and Finance
What testing/CI practices do you enforce for a dbt-based pipeline
How have you mentored analytics engineers on modeling best practices
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