Senior / Staff Data Platform Engineer

Company: Radar Labs

Location: New York, NY (Remote)

Salary: $200,000 - $300,000 a year

Type: Full-time

Remote: Yes

Posted: 2026-05-04

About this role

## Location

New York ; US Remote

## Employment Type

Full time

## Location Type

On-site

## Department

Engineering

## Compensation

  • $200K – $300K • Offers Equity

About Radar

Radar is the global leader in geolocation, with geofencing SDKs, maps APIs, and AI-enabled solutions for marketing, fraud, and operations teams.

Why is Radar the best place to work?

  • We're trusted by some of the world's best companies, from high-growth startups to the Fortune 500.
  • We have incredible scale: We're processing over 1 billion API calls per day from hundreds of millions of devices.
  • We're well-resourced, and we've raised $85.5M from world-class investors, including Accel and Insight Partners.
  • We have a high-performance culture, with ambitious and entrepreneurial teammates in every role.
  • We recently moved into an amazing new office in Flatiron, Manhattan, NYC.
  • We were recently named a top 10 best place to work in NYC by Crain's.

Despite our growth and scale, we're still just getting started. That's where you come in.

About the role

We're looking for a Data Platform Engineer to build out the next generation of our data platform . The ideal candidate has been a data platform engineer on a large system and is energized by deeply understanding customer pain points and opportunities related to our data platform. To date this has been a shared responsibility on our engineering team, but as we've grown to over 1 billion API calls per day (with lots of data exhaust into our data lake), we're hiring a Data Platform Engineering team to modernize and level up our data stack. This role can be either in our NYC HQ or remote in the US.

How we work:

Most of our engineering team are former technical co-founders or former Radar interns from schools like Waterloo and CMU. Most engineers at Radar fit one of two molds, technically: either Staff level expertise in one stack, or "Multi-Stack" at any level. We say "Multi-Stack" because "Full-Stac...

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