Analytics Engineer at Pave

San Francisco, California, United States

Pave Logo
Not SpecifiedCompensation
Mid-level (3 to 4 years)Experience Level
Full TimeJob Type
UnknownVisa
Technology, HR TechnologyIndustries

Requirements

  • Product Mindset - Intuitive understanding of how data pipeline decisions affect downstream user experience
  • Scalability - Ability to design and implement robust, scalable systems for future growth and evolving use cases
  • Bias for Action - Catalyst and accelerator who unblocks self and others while making strategic trade-offs
  • Experience - 4+ years in a Data/Analytics Engineering role, ideally product-facing; proficiency with dbt and Airflow; familiarity with cloud data warehouses
  • Exposure to ML workflows - Collaboration with data scientists or ML engineers to transform features, create training datasets, deploy, and monitor models
  • Track record of impact

Responsibilities

  • Extend and maintain core data models that power Pave's compensation intelligence products
  • Design scalable data pipelines that support production use cases across the product suite, with emphasis on Market Data
  • Own data observability by implementing monitoring, testing, and validation frameworks to maintain trust in the dataset as it scales
  • Collaborate cross-functionally with data scientists, product managers, and software engineers to translate product needs into customer insights
  • Help drive millions of dollars of revenue growth

Skills

TypeScript
Node.js
React
GCP
Machine Learning
AI

Pave

Compensation management solutions for businesses

About Pave

Pave provides compensation management solutions designed for businesses of all sizes, particularly those backed by venture capital. Its main product is a suite of tools that integrate with existing HR Information Systems (HRIS), Applicant Tracking Systems (ATS), and Cap Table software, allowing companies to access real-time data for employee compensation planning and benchmarking. This integration helps eliminate the need for spreadsheets and manual data entry, enabling HR leaders to make informed decisions based on accurate information. Pave operates on a subscription-based model, offering various tiers that may include advanced analytics and personalized support. The company aims to simplify the compensation analysis process, making it easier for HR departments to ensure fair and competitive pay, which can lead to improved employee satisfaction and retention.

New York City, New YorkHeadquarters
2019Year Founded
$165.4MTotal Funding
SERIES_CCompany Stage
Data & Analytics, Enterprise SoftwareIndustries
1-10Employees

Benefits

Competitive salary
Equity
Medical, dental & vision coverage
Commuter benefits
Catered lunch
Unlimited PTO policy

Risks

Competition from established HR tech companies like Workday and ADP is intensifying.
Data privacy concerns may arise from integrating with multiple HR systems.
Economic downturns could impact Pave's growth due to reliance on VC-backed clients.

Differentiation

Pave offers real-time compensation data, eliminating the need for spreadsheets.
Seamless integration with HRIS, ATS, and Cap Table systems sets Pave apart.
Pave's platform is powered by the largest real-time compensation dataset globally.

Upsides

Partnership with UKG enhances Pave's platform with valuable organizational data.
Pave's subscription model aligns with growing trends in enterprise software.
Increased focus on pay equity boosts demand for Pave's data-driven solutions.

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