At Pave, we believe the world of compensation is broken, and we’re going to fix it. Today, teams cobble together hundreds of messy spreadsheets and outdated surveys to determine how to compensate their employees. At best, they’re leveraging stale data from an industry that is quickly evolving past it. Add COVID, a new remote and distributed workforce, and you have an even blurrier picture of what “market compensation” is, how it’s evolving, and how to communicate it to employees.
That’s where we come in. Pave allows companies to benchmark compensation to leaders in their industry, analyze internal compensation data and make the right adjustments, then visually communicate compensation to their employees. We’re building the world’s largest real-time compensation data platform on the path to help employers and employees navigate the murky world of compensation with clarity, equity, and accessibility. And you don’t have to just hear it from us — you can hear it from our customers: Allbirds, Hover, Shopify, Discord and more.
Our Team: With amazing growth comes amazing engineering challenges. We're looking for talented software engineers to build amazing products, while supporting complex data infrastructure.
You'll have the opportunity to champion initiatives and directly shape culture. Pave sits in the sweet spot of project ownership and support, with talented engineers from the likes of Apple, Facebook, and Uber.
Your Primary Focus: • Work with our product teams to build a best-in-class API and data layer to power our products. • Partner with other engineers to scale our infrastructure, data pipeline, and unlock new product value. • Partner with business stakeholders to solve meaningful problems for our customers.
About You: • 3+ years of experience building scalable and service oriented applications • Excited by the idea of championing projects end-to-end • Experience with Cloud infrastructure (e.g. AWS, GCP) and API layers (e.g. GraphQL) • Experience working with authentication & authorization controls • Scaled production systems to handle large volume • Worked with data pipelines and complex data systems
Our Tech Stack: • Typescript, React, and Node.js • GCP Firestore, Cloud Run, and BigQuery