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 Today, teams cobble together hundreds of messy spreadsheets and outdated surveys to determine how to compensate their employees.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: The mission of the Data team at Pave is to leverage the rich data produced by the Pave ecosystem to enable Pave to provide the most valuable insights to its users as well as to serve as the core optimization engine for the company. We build data infrastructure, define and evaluate metrics of success, derive actionable insights, and build predictive models to enable a culture of data-driven decision making and optimize every aspect of our business.
Your Primary Focus: • Creating and maintaining data pipelines to support analytics, metrics reporting, machine learning, product features, and more • Managing necessary infrastructure to ensure the team is able to execute its primary role • Designing and maintaining our data warehouse • Maintaining and developing tooling to support our Data team • Drive technical excellence across the entire Data team
About You: • 4-6+ years of experience in a data engineering or similar functional role • Bachelor’s degree or advanced degree in a quantitative discipline: Computer Science, Math, Statistics, Engineering, or a related field • Expert knowledge of Python and SQL • Exceptional knowledge of data warehouse design and management • Experience with visualization tools such as Looker or Tableau • Strong communication skills • Comfortable working in fast-paced environments