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Vercel

Software Engineer, Data Platform

Hybrid - San Francisco, New York City$130k–$200kmidAdded today

About this role

Vercel seeks a Data Platform Engineer to build and maintain the streaming, storage, and tooling infrastructure that powers data across the company. Working with technologies like Kafka, ClickHouse, Tinybird, and Snowflake, you'll design reusable systems for data ingestion, movement, and serving while learning from senior engineers at scale.

What you'll do

  • Develop and maintain streaming systems and storage layers using Kafka, ClickHouse, Tinybird, and Snowflake
  • Build reusable infrastructure and internal abstractions that enable self-service data access for other teams
  • Implement monitoring, alerting, and observability to detect and prevent platform issues
  • Design and enforce access controls, data protection, and compliance practices across the platform
  • Contribute to architecture decisions and build-vs-buy evaluations at the platform level
  • Develop features and fixes with increasing independence while incorporating code review feedback

What they're looking for

  • Programming in Python, Java, Scala, Go, or similar infrastructure-focused languages
  • Distributed systems and event-driven architecture design
  • Kafka and real-time streaming technologies
  • SQL and query optimization
  • ClickHouse or Snowflake data warehouse experience
  • Systems monitoring and observability tooling
  • Data pipeline architecture and schema design
  • Collaborative problem-solving and technical communication
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Vercel

Vercel builds a global content delivery platform and developer infrastructure centered on modern web frameworks like Next.js, along with AI-powered workflow and agent platforms. The company is hiring software engineers across infrastructure, full-stack, open-source, and AI teams to work primarily with TypeScript, Go, React, and Lua on performance optimization, developer tools, and intelligent automation features.

Website
vercel.com
View all jobs at Vercel

Likely interview questions

  • Describe your experience with Kafka or other streaming platforms—what challenges have you encountered when moving data in real-time at scale?
  • Walk us through how you'd approach designing a reusable data ingestion framework that other teams would build on top of.