Analytics Engineer
Join Pave as an Analytics Engineer to redefine compensation insights with real-time data and scalable solutions.
Posted by employer 3 months ago
First seen on Joblaze 1 month ago
Last verified on the company career page 14 hours ago
Skills & Technologies
AI in the day-to-day
Our platform combines real-time compensation data with expertise in AI and machine learning.
Requirements
- Experience
- 4+ years
Not disclosed in this posting: visa sponsorship.
Benefits
Joblaze summary
In the role of Analytics Engineer at Pave, the individual will focus on extending and maintaining data models that drive the company's compensation intelligence products. Key skills include proficiency in dbt and Airflow, along with experience in designing scalable data pipelines and collaborating with cross-functional teams. This position is ideal for someone with over four years of experience in data or analytics engineering, particularly in product-facing roles. Pave's culture emphasizes teamwork and a commitment to high standards, making it a fitting environment for driven professionals.
Joblaze insights
- Listed about a month ago — first seen on Joblaze September 3, 2026. Last confirmed on Pave's careers page October 27, 2026.
- Salary band is in line with the typical range for Data Engineering roles (median ~$180,656).
- Starts above 77% of 13 comparable mid data engineering roles in United States that list dbt we track (median $150,000 across 9 companies). See dbt salary trends
- dbt appears in 31.2% of 77 comparable mid data engineering roles in United States; Airflow appears in 29.9% of 77 comparable mid data engineering roles in United States.
Quick facts
- Is the Analytics Engineer role remote?
- It's hybrid — Pave expects some on-site time in San Francisco, CA.
- What's the salary range?
- Pave lists $169,000–$222,000 for this role.
- How much experience is required?
- At least 4 years of relevant experience for this Analytics Engineer role.
- Where is the role based?
- Pave is hiring for this position in San Francisco, CA.
- What's the tech stack?
- Joblaze extracted these technologies from the posting: Airflow, Cloud Data Warehouses, dbt.
- What seniority level is this role?
- Pave targets mid-level candidates for this position.
- Is this full-time or contract?
- Full-time for this Analytics Engineer role at Pave.
From the original posting
Who We Are
The Data Team @ Pave
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 supported 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
P3: $169,000 - $194,000
P4: $202,000 - $222,000
Life @ Pave
Standard company text repeated across Pave's postings is omitted here.