Twilio
Staff Business Intelligence Engineer
Remote Finance role with clear candidate location fit.
PostedRecently added
Eligible countries1 accepted country
Seniority signalLead
Work settingRemote
Accepted candidate locations
India
Role overview
Staff Business Intelligence Engineer
Requirements and responsibilities
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Details
- Own and evolve Twilio's suite of business intelligence tools, driving governance, performance, and long-term roadmap decisions
- Design and build scalable, reusable dashboards and reports that surface actionable insights for stakeholders across legal, billing operations, and other mission critical business functions
- Architect and deploy agentic AI solutions that enable natural language querying, automated insight generation, and self-service analytics for non-technical business partners
- Collaborate with data engineers, business partners, and AI/ML engineers to translate complex analytical requirements into reliable, well-documented data products
- Establish and champion BI best practices, including semantic layer design, metric definitions, data access governance, and documentation standards
- Partner with business leaders to identify opportunities where better data visibility can drive meaningful outcomes, and prioritize accordingly
- 7+ years of experience in business intelligence, data analytics, or a related field, with at least 2 years in a staff or senior individual contributor role
- Proven experience managing and administering enterprise BI platforms (Tableau, Looker, Superset, or similar)
- Strong SQL skills and experience with data modeling in a modern data warehouse (e.g., Snowflake, Athena, etc.)
- Track record of delivering self-service analytics capabilities that reduced dependency on centralized data teams
- Experience working directly with business stakeholders to define requirements and translate them into scalable data products
- Experience with dbt or similar semantic/transformation layers
- Familiarity with Python for analytics automation or data pipeline work
- Experience with LLMs, AI agents, or other AI technologies applied to analytics use cases
- Familiarity with data governance frameworks and access control best practices
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