Lead Analytics Engineer

About Reve Labs, Inc

Revv is a B2B SaaS company revolutionizing the auto collision industry with AI and machine learning solutions that streamline processes and improve road safety. Our mission is to reduce collisions and create a safer transportation future.
Revv ADAS is an AI platform that automates the complex research needed to understand Advanced Driving Assistance Systems (ADAS) for auto repair businesses. The ADAS market is growing rapidly, expected to rise from $64 billion to over $212 billion by 2034, driven by software innovations.
Backed by a Series A investment led by Left Lane Capital and others, Revv has raised over $13 million in its first year, positioning itself for rapid growth. Are you ready to lead a technological revolution in an industry ripe for change? Revv is at the forefront of delivering cutting-edge software that delights customers.

About the role

As the Lead Analytics Engineer, you will play a pivotal role in defining the Analytics function at Revv, and be responsible for establishing a scalable data warehouse, modeling data for consumption by various stakeholders in the business, and defining best practices with our data for years to come.
The ideal candidate will be opinionated and driven to apply their expertise to create a best-in-class Analytics organization in a fast-growing environment, using both tools from the modern data stack (dbt, Fivetran/Airbyte, Metabase/Looker, etc) as well as Python and shell scripts with a focus towards getting the job done.

What you'll do

• Establish a data warehouse: Work with our engineering team to build a data warehouse from the ground up, providing recommendations and hands-on expertise for warehouse selection and CI/CD. Use low- and no- code ELT tools like Fivetran to pull data from our various sources (Stripe, Salesforce, Postgres) into the warehouse.
• Collaborative data modeling: Craft intuitive and user friendly data models in dbt to meet stakeholder requirements for finance, product, and sales teams to draw insights from our data using SQL and data exploration tools like Metabase.
• Foster a self-serve analytics culture: Set up analytics tooling and documentation that enables self-service for stakeholders across the business.
  

Qualifications

• Expertise with SQL & dbt a must-have
• Proficiency with Python or equivalent
• 5+ years of experience in Analytics Engineering, Data Engineering, or Data Analytics roles
• Skilled in dimensional and reporting data models (dimension & fact tables, time series aggregations, etc)
• High attention to detail and a compulsion for data governance, documentation, and …