Senior Software Engineer (L3) – Segment Data Pipelines
Twilio · Remote
| Company | Twilio |
|---|---|
| Role | Senior Software Engineer (L3) – Segment Data Pipelines |
| Location | Remote |
| Work mode | Remote |
| Experience | 3–6 years |
| Job type | Full-time |
| Qualification | Bachelor's or Master's degree in Computer Science, Engineering or a related field |
About this job
Twilio is hiring a Senior Software Engineer (L3) for the Segment Data Platform and Pipelines team. The team builds the systems that pull customer data in from many sources and route it out to downstream tools, handling hundreds of thousands of events every second.
This is a remote-first role open to candidates living in Delhi, Karnataka, Maharashtra, Telangana or Tamil Nadu, with occasional travel for team meetings. You will design high-scale routing features, run them in production, mentor junior engineers and join an on-call rotation.
Eligibility
- 5 to 7 years of experience writing production code in a modern language
- Strong Go, Java, Python or a similar object-oriented language
- Hands-on work with high-volume messaging or streaming systems and processing engines
- Experience running large distributed systems on cloud infrastructure and shipping through CI/CD
- Must live in one of the five permitted Indian states
Skills required
What you will do
- Design and deliver reliable, high-scale data routing for Segment pipelines
- Operate always-on distributed services in the cloud and take part in on-call
- Shape solutions with product, design and fellow engineers, weighing usability, speed and long-term design
- Explain technical decisions and trade-offs clearly to the team
- Mentor junior engineers and improve operational tooling and reliability
How to apply
- Open the official Twilio job page with the Apply button and submit your application there.
- Tailor your resume to streaming systems, event volumes and the distributed services you have built and run in production.
Before the interview, prepare:
- Streaming fundamentals: partitions, ordering, back-pressure and at-least-once vs exactly-once delivery
- Distributed system design: design an event router that fans data out to many destinations with retries
- Kubernetes and cloud operations: deployments, autoscaling and how you debug a noisy production service
- On-call stories: one incident you handled end to end, with root cause and the fix you shipped
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