Analytics Engineer

About the role

As part of the Data team at Pave you will help redefine how companies understand the labor market and determine compensation. You’ll 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), and own data observability by implementing monitoring, testing, and validation frameworks that maintain trust in our dataset as it scales.

You’ll collaborate cross-functionally with data scientists, product managers, and software engineers to translate product needs into insights that support our thousands of customers and help drive millions of dollars of revenue growth.

Responsibilities

• 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

Requirements

• 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.
• 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.

Benefits

• Comprehensive medical, dental, and vision coverage for you and your family, with a range of options designed to meet you where you are.
• Flexible PTO and the freedom to work from anywhere in the world for up to a month.
• Lunch and dinner stipends plus fully stocked kitchens.
• Quarterly education stipend to invest in the skills and knowledge that matter most to you.
• Robust parental leave so you can be fully present for the moments that count.
• Commuter stipend to support in-person collaboration.

Pay

Your total rewards package includes meaningful equity and best-in-class medical, dental, and vision coverage. Your level and compensation are determined by your experience and how you show up throughout the interview process.