Senior Analytics Engineer

At Twilio, we’re shaping the future of communications, all from the comfort of our homes. We deliver innovative solutions to hundreds of thousands of businesses and empower millions of developers worldwide to craft personalized customer experiences.

Our dedication to remote-first work, and strong culture of connection and global inclusion means that no matter your location, you’re part of a vibrant team with diverse experiences making a global impact each day. As we continue to revolutionize how the world interacts, we’re acquiring new skills and experiences th...

We use Artificial Intelligence (AI) to help make our hiring process efficient. That said, every hiring decision is made by real Twilions!

In this role, you’ll:
Design and implement a formal analytics data layer using AWS Glue, Athena / Presto, and LookML
Collaborate within the Data Science & Analytics team and across Product & Engineering to define, document, and maintain alignment on metric definition and data lineage
Develop and maintain automated data reconciliation and quality checks to proactively identify and resolve discrepancies, ensuring accuracy and consistency of critical reports and dashboards
Lead investigations into complex data anomalies, conduct root cause analysis, and communicate findings and solutions effectively to both technical and non-technical audiences
Mentor and guide members of the data science and analytics team, establishing and enforcing best practices around data modeling, testing, documentation, and code review

Twilio values diverse experiences from all kinds of industries, and we encourage everyone who meets the required qualifications to apply. If your career is just starting or hasn't followed a traditional path, don't let that stop you from considering Twilio. We are always looking for people who will bring something new to the table!
4-5 years of professional experience in analytics engineering, data engineering, or a related discipline
Strong expertise in SQL and hands-on experience designing data models and orchestrating data pipelines using AWS Glue or similar technologies
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 owning ambiguous projects from beginning to end with minimal guidance
Strong technical communication and mentorship skills, with the ability to convey complex concepts to a range of audiences

 
Desired:
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 like Hive, Presto, and Spark; and dashboarding tools like Looker or Tableau
Proven track record of implementing robust data quality and testing frameworks, including expertise with dbt tests, CI/CD, and data observability
Experience evangelizing and establishing data culture and best practices within a fast-paced technology organization