Quick Summary
Who We Are At Pave, we're building the industry’s leading compensation platform, combining the world's largest real-time compensation dataset with deep expertise in AI and machine learning.
At Pave, we're building the industry’s leading compensation platform, combining the world's largest real-time compensation dataset with deep expertise in AI and machine learning. Our platform is perfecting the art and science of pay to give 8,500+ companies unparalleled confidence in every compensation decision.
Top tier companies like OpenAI, McDonald’s, Instacart, Atlassian, Synopsys, Stripe, Databricks, and Waymo use Pave, transforming every pay decision into a competitive advantage. $190+ billion in total compensation spend is managed in our workflows, and 70% of Forbes AI 50 use Pave to benchmark compensation.
The future of pay is real-time & predictive, and we’re making it happen right now. We’ve raised $160M in funding from leading investors like Andreessen Horowitz, Index Ventures, Y Combinator, Bessemer Venture Partners, and Craft Ventures.
As part of the Data team at Pave you will help us redefine how companies understand the labor market and determine compensation. Even the most innovative tech companies in the world often use spreadsheets full of flawed statistics to determine how to pay. At Pave we’ve built a system of real-time integrations that allow us to bring best practices from machine learning, data science, software tooling, and AI to an industry that is built on data, but doesn’t have the tools it needs to fully leverage it.
Responsibilities
~1 min read- →Extend and maintain core data models that power Pave's compensation intelligence products
- →Design scalable data pipelines that support production use cases across our product suite, with an emphasis on Market Data
- →Own data observability by implementing monitoring, testing, and validation frameworks that maintain trust in our dataset as it scales
- →Collaborate cross-functionally with data scientists, product managers and software engineers to translate product needs into insights that supported our thousands of customers
- →Help drive millions of dollars of revenue growth
- Product Mindset - You want to be a core contributor in building and maintaining the data infrastructure for a product. You intuitively understand how decisions made within the data pipeline affect the user experience downstream.
- Scalability - You design and implement systems that are robust and scalable, ensuring they can efficiently handle future growth and evolving use-cases.
- Bias for Action - You’re a catalyst and an accelerator. You’re constantly unblocking yourself and others while making strategic trade-offs.
- Experience - 4+ years of experience in a Data/Analytics Engineering role, ideally in a product-facing capacity. Proficiency with dbt and airflow, and familiarity with cloud data warehouses.
- Exposure to ML workflows - you've collaborated with data scientists or machine learning engineers to transform features, create training data sets, and deploy and monitor models
- Track record of impact - you've shipped data products or infrastructure that meaningfully improved business outcomes and end user experiences
What We Offer
~2 min readAt Pave, we believe compensation should be as thoughtful as the people we hire. Your total rewards package includes meaningful equity, best-in-class medical, dental, and vision coverage, unlimited PTO, and region-specific benefits designed around your life — not just your role. Your level and compensation are determined by your experience and how you show up throughout the interview process. We're always happy to walk you through how we think about leveling — just ask.
At Pave, growth isn't a perk — it's the point. As you develop, your role expands, your responsibilities deepen, and your compensation reflects the impact you're making.
Founded in 2019 with a clear purpose and a team that has never wavered from it, Pave has grown into a global force in compensation management — giving thousands of companies the tools to take control, build confidence, and earn credibility in every pay decision they make. And we're just getting started. Headquartered in San Francisco's Financial District, with regional hubs in New York City's Flatiron District, Salt Lake City, Kraków (Poland), and the United Kingdom — wherever you're based, you'll find the same thing: people who genuinely care about the work, each other, and the customers that rely on Pave.
We run a hybrid culture that brings teams together in person 3 to 4 days a week — and every Friday, the whole company gathers for our Team Sync: breakfast, new hire welcomes, product updates, fireside chats, and yes, the occasional Kahoot. It's one of the things people notice when they join us — that we truly enjoy spending time together.
Our culture is shaped by five values we live every day:
- Be Intellectually Honest — Truth over comfort. We face reality clearly and speak directly, even when it's hard.
- Play to Win — We're not here to participate. We're here to be the #1 compensation platform in the world, and we act like it.
- Uphold the Pave Platinum Standard — We hold ourselves to the highest bar — for our customers, our data, and each other.
- One Team — We win and lose together. Titles don't drive decisions here — shared goals do.
- Hug of Jawn — Hard to define, impossible to miss. Ask your recruiter.
Our Vision: Unlock a labor market built on trust.
Our Mission: Build confidence in every compensation decision.
We build software that transforms how companies pay their people — and we believe the team behind that software deserves the same thoughtfulness. If you're ready to help shape the future of compensation alongside people who are smart, humble, and genuinely motivated by the problem we're solving, we'd love to meet you.
Still deliberating? Just apply! We're always excited to meet people who are eager to contribute.
Location & Eligibility
Listing Details
- Posted
- July 21, 2026
- First seen
- July 21, 2026
- Last seen
- July 23, 2026
Posting Health
- Days active
- 0
- Repost count
- 0
- Trust Level
- 60%
- Scored at
- July 21, 2026
Signal breakdown
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