Data Engineering Lead

Why join Pave?

At Pave, our vision is simple - Make Compensation Fair. 

How are we going to get there? By building the most intelligent compensation platform, powered by the largest real-time compensation dataset on earth.

We partner with our customers to help them build and retain world-class teams through planning, communicating and benchmarking their team’s compensation in real time.  And you don’t have to just hear it from us — you can hear it from our customers: Hover, Plaid, Fanduel and more! 

We’re growing fast, building an incredible team and product, and having plenty of fun as we do it in our San Francisco and New York City offices. 

If operating with intellectual honesty, playing to win, and focusing on upholding a platinum standard sounds exciting - we highly encourage you to reach out. We’d love to partner on our journey to change the world of compensation! 

Data Team @ Pave

Data is truly at the heart of what we do here at Pave.

So, it’s no surprise that Pave Data Engineers are integral collaborators and strategic owners with company-wide impact, enabling us to build a stellar product experience.

Our Data Engineering Lead will partner closely with data scientists, software engineers, and product managers to craft the systems that enable us to serve compensation insights to thousands of customers, influencing $100+ billion in total compensation.

They’re not only responsible for designing and maintaining robust data pipelines and models but also establishing the vision for the infrastructure that powers our product.

What we're looking for

• Product Mindset: You’ve been 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 your team while making strategic trade-offs.
• 8+ years of experience in a Data/Analytics Engineering role, ideally in a product-facing capacity. Strong software engineering experience and architectural experience is desired.
• 2+ years of experience leading teams in a people management or tech lead capacity.
• Exceptional data manipulation and modeling skills with proficiency in SQL and Python.

What you'll get out of it 

• Impact: Your work will impact billions in compensation spend by influencing decisions made in offices and boardrooms worldwide.
• Ownership: You’ll own major technical initiatives from end-to-end with the support of your incredible teammates and collaborators.
• Visibility: Play a key role in establishing the company as an authority in comp tech through building the infrastructure that supports new features, products, and insights.

Compensation, It's What We Do.

This salary range may include multiple levels. 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. 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, commuter benefits, catered lunch, an unlimited PTO policy, and many other region-specific benefits.Pave's salary range for this position $221,000—$299,000 USD

Our Compensation Philosophy

Pave’s compensation philosophy is to target the 75th percentile of the market for both cash and equity at your job level.  This means that the “mid point” of every band at Pave is the 75th percentile of the broader market.

Pave also has a merit-based philosophy when it comes to compensation increases. We run a performance cycle twice per year to evaluate employees’ performance. Higher than average performance ratings result in compensation increases to the upper end of the individual’s compensation range for their role. The result is that high performers at Pave are paid <