Senior Analytics Engineer

Twilio•,

124d•$141,520 - $208,000•Remote

About The Position

Twilio is hiring a Senior Analytics Engineer, R&D, to improve the consistency and quality of its R&D analytics data layer and accelerate analysts’ development velocity. The role is part of the Data Science and Analytics team, which supports R&D decision-making with trusted data that helps accelerate innovation and improve product performance. The engineer will work with the team and with Product and Engineering to design and maintain an analytics data layer that supports reliable reporting on R&D metrics. The role is remote, though occasional in-person attendance may be requested for team gatherings, functional off-sites, customer meetings, or project meetings. The position is not eligible for hiring in California, Connecticut, New Jersey, New York, Pennsylvania, or Washington. Occasional travel may be required. Twilio offers competitive pay, time off, parental and wellness leave, healthcare, a retirement savings program, and other benefits that vary by location. The position may be eligible for Twilio’s equity plan and corporate bonus plan. Applications are intended to be accepted until August 10, 2026, subject to change based on business needs.

Requirements

4–5 years of professional experience in analytics engineering, data engineering, or a related discipline.
Strong SQL expertise and hands-on experience designing data models and orchestrating data pipelines using AWS Glue or similar technologies.
Ability to partner with cross-functional stakeholders to codify, document, and reconcile critical business metrics and ensure company-wide data alignment.
Track record of owning ambiguous projects from beginning to end with minimal guidance.
Strong technical communication and mentorship skills, including the ability to convey complex concepts to varied audiences.

Nice To Haves

5+ years of professional experience in analytics engineering, data engineering, business intelligence, or a related discipline, ideally in a B2B SaaS environment.
Expertise in Python, distributed computing technologies such as Hive, Presto, and Spark, and dashboarding tools such as Looker or Tableau.
Track record of implementing robust data quality and testing frameworks, including expertise with dbt tests, CI/CD, and data observability.
Experience promoting and establishing data culture and best practices in a fast-paced technology organization.

Responsibilities

Design and implement a formal analytics data layer using AWS Glue, Athena/Presto, and LookML.
Collaborate with the Data Science and Analytics team and Product and Engineering to define, document, and maintain alignment on metric definitions and data lineage.
Develop and maintain automated data reconciliation and quality checks to identify and resolve discrepancies and ensure accuracy and consistency in critical reports and dashboards.
Lead investigations into complex data anomalies, perform root cause analysis, and communicate findings and solutions to technical and non-technical audiences.
Mentor and guide data science and analytics team members and establish and enforce best practices for data modeling, testing, documentation, and code review.