Analytics Lead

Who we are

About Privy

Our mission is to make privacy and user ownership the default online. We build simple, flexible developer tooling that make it easy to build products that put users first. By leveraging modern cryptography, we shift the status quo around digital ownership and protect the accounts and assets of millions of users.

Learn more about Privy: Privy and Stripe: Bringing crypto to everyone

What you’ll do

Analytics at Privy is not just about running queries or building reports. We transform messy, high-volume data into scalable systems and clear insights that guide product decisions and business strategy. We design pipelines that are resilient, models that are intuitive, and tools that make data accessible and trustworthy for everyone across the company. We believe in clean abstractions, transparency, and sharing our work so teammates can build on top of it. We push each other to ask sharper questions, test bold ideas, and follow the signal in the data so we can shape better products and empower our customers.

Who you are 

• 8+ years in an analytics engineering or data engineering role, preferably in a SaaS environment.
• Proficiency in SQL and data modeling techniques.
• Experience with ETL processes and tools (e.g., Airflow, dbt, or similar).
• Familiarity with analytics tools like Looker, Tableau, or similar BI platforms.
• Experience working with cloud data storage solutions (AWS, GCP, etc.).
• Familiarity with product analytics tools (e.g., Amplitude, Mixpanel). 
• Ability to translate business requirements into analytical solutions.
• Comfortable working with cross-functional teams, presenting technical insights to non-technical stakeholders.

Preferred qualifications

• Experience in an API-based business and in payments, fintech, or crypto.
• Experience with usage-based pricing models and understanding of how complex queries impact customer billing.
• Experience in launching new products in fast-paced, scaling environments.
• Experience with data governance and ensuring data quality at scale.