Senior Analytics Engineer

Twilio

2h•$141,520 - $208,000•Remote

About The Position

Twilio is seeking a Senior Analytics Engineer for its R&D organization. The role advances the consistency and quality of the R&D analytics data layer and helps analysts work more efficiently. The Data Science and Analytics team empowers R&D to make data-backed decisions that accelerate innovation and improve product performance. The engineer will work with the team and with Product and Engineering to design and maintain a robust analytics data layer for trusted reporting on R&D metrics. The position is remote, but is not eligible for hiring in California, Connecticut, New Jersey, New York, Pennsylvania, or Washington. Occasional travel may be required for in-person project or team meetings. Employees may also be asked to attend in-person team gatherings, functional off-sites, or customer meetings on an ad-hoc basis. Twilio offers competitive pay, generous time off, parental and wellness leave, healthcare, a retirement savings program, and other benefits. Specific offerings vary by location. The role may also be eligible for Twilio’s equity plan and corporate bonus plan. Applications are intended to be accepted until August 10, 2026, though this date may 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.
Demonstrated ability to own ambiguous projects from beginning to end with minimal guidance.
Strong technical communication and mentorship skills, including the ability to convey complex concepts to a range of 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.
Experience implementing robust data quality and testing frameworks, including dbt tests, CI/CD, and data observability.
Experience promoting and establishing data culture and best practices within 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 accurate, consistent 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.