Analytics Engineer

Analytics Engineer

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 58% 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.

Pave's R&D pillar includes our data science, engineering, information technology, product design, product management, and security teams. This organization builds, maintains, and secures a platform used by more than 8,500+ client organizations.

Our engineering team moves between ideation, scoping, and execution in a matter of days while closely iterating with cross-functional partners on requirements. At Pave, we use TypeScript, Node.js, and React, hosted on GCP.

Compensation strategy is broken down into three pillars - compensation bands, planning workflows, and total rewards communication. We build products that make these processes seamless for customers.

Over the next year, our roadmap is focused on enhancing the entire compensation lifecycle: from philosophy definition to market trend analysis, band adjustments, merit cycles, and employee communication. We're seeking passionate engineers who are excited about building robust, data-rich systems that simplify complex compensation processes at scale.

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.

What You'll Do

• 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 support our thousands of customers
• Help drive millions of dollars of revenue growth

What You'll Bring

• 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

Compensation, It's What We Do.

Salary is just one component of Pave's total compensation package for employees. Your total rewards package at Pave will include equity, top-notch medical, dental, and vision coverage, an unlimited PTO policy, and many other region-specific benefits. Your level is based on our assessment of your interview performance and experience, which you can always ask the hiring manager about to understand in more detail. This salary range may include multiple levels.

The targeted cash compensation for this position is (level depends on experience and performance in the interview process):

P3: $195,000 - $215,000

P4: $230,000 - $250,000

Life @ Pave

Since being founded in 2019, Pave has established a robust global footprint. Headquartered in San Francisco's Financial District, we operate strategic regional hubs across New York City's Flatiron District, Salt Lake City, and the United Kingdom. We cultivate a vibrant, collaborative workplace culture through our hybrid model, bringing teams together in-person on Mondays, Tuesdays, Thursdays, and Fridays to foster innovation and strengthen professional relationships.

Benefits @ Pave

At Pave, career advancement drives everything—roles expand, responsibilities deepen, and compensation rises alongside your professional growth.

What we provide

• Complete Health Coverage: Comprehensive Medical, Dental and Vision coverage for you and your family, with plenty of options to suit your needs
• Time off & Flexibility: Flexible PTO and the ability to work from anywhere in the world for a month
• Meals & Snacks: Lunch & dinner stipends as well as fully stocked kitchens to fuel you
• Professional Development: Quarterly education stipend to continuously grow
• Family Support: Robust parental leave to bond with your new family
• Commuter Assistance: A commuter stipend to help you collaborate in person

Vision - Our vision is to unlock a labor market built on trust

Mission - Our team's mission is to build confidence in every compensation decision

Are you ready to help our customers make smarter, more effective compensation decisions?