Remote (US) · Eastern Time collaboration hours · Full-time
About us
Revv is on a mission to revolutionize the global auto repair industry and shape the future of safer, smarter roads. In August 2026, Revv merged with AirPro Diagnostics, a premier provider of remote automotive diagnostics and ADAS calibration solutions, bringing together two industry leaders to create a comprehensive, end-to-end ADAS platform. The combination pairs Revv’s AI-powered software and proprietary automotive knowledge graph with AirPro’s diagnostic expertise, hardware, calibration technology, and nationwide service capabilities.
With the combined scale, technology, and industry expertise of Revv and AirPro, we have an opportunity to define the next generation of automotive repair technology. Read more about the merger here!
Why this role matters
We've just combined two businesses, two clouds, and more than ten years of operating data. We believe the shared data across Revv and AirPro is one of the most strategically important assets. That data already powers customer-facing products, such as our AI that identifies which ADAS calibrations a vehicle needs, and it is the foundation for how we understand and run the business.
We're looking for a senior or staff-level data engineer who can walk into a complex, multi-cloud environment, make sense of it quickly, and chart a practical path forward. You'll have real ownership and not much hand-holding. We value momentum over perfection and clarity over cleverness.
What you'll do
Assess and set the strategy. In your first months, map data needs across engineering, product, finance, sales, and operations, evaluate the current state of our infrastructure, and lay out a plan for a data platform that scales across AWS and Azure.
Integrate two companies' data. Bring AirPro's production data (SQL Server on Azure) into our Snowflake data lake alongside Revv's existing AWS → Fivetran → dbt → Snowflake pipelines. We're considering Azure Synapse for this; you'll pressure-test that choice and own the architecture.
Model data the business can trust. Build clean, tested, well-documented dbt models that our analytics team builds on in Power BI and Hex.
Connect our business systems. Partner with finance and sales to integrate Salesforce and our ERP so revenue and operating metrics are consistent across the company.
Define the foundations. Help establish how we handle data governance, quality, and ownership, including our SOC 2 and international data handling requirements.
Turn data into an asset. As the integration matures, help shape how connected data across every customer touchpoint becomes new products and better experiences for the shops we serve.
Who you'll work with
You'll report to our Head of Product Analytics, with a dotted line to engineering leadership on the AirPro platform side. You'll partner daily with our analytics team and regularly with finance, sales, and product leadership.
What we're looking for
Typically 6+ years in data engineering, including ownership of platform-level design decisions.
Deep, hands-on production experience with Snowflake and dbt.
Strong Python and SQL.
Working familiarity with the Azure data ecosystem (SQL Server, Data Factory, Synapse, or similar). You don't need to be an Azure specialist, but you shouldn't be starting from zero.
Sound architectural judgment: you weigh tradeoffs in ingestion, orchestration, and modeling, and can explain clearly why you'd choose one path over another.
Comfort with ambiguity. You've walked into situations without a playbook, figured out what mattered most, and made progress without waiting for perfect information. When you're blocked, you find a way around it.
A habit of making your work understandable. You document models, decisions, and strategy so that people outside engineering can use and trust the data.
Experience partnering across functions and translating business questions into data requirements, and back again.
Experience at a SaaS or software company.
Nice to have
Building data that powers customer-facing products, including ML or AI features.
Integrating data across clouds or after an acquisition or merger.
Fivetran and modern orchestration tools (Airflow, Dagster, or similar).
Establishing data governance, SOC 2 controls, or data residency practices.
No automotive or insurance background is required.
What success looks like
90 days: You've mapped our data needs and current state and shared a clear, pragmatic plan for data infrastructure that leadership has bought into.
6 months: Revv and AirPro data is integrated and accessible enough that teams are getting insight across the combined business. Not perfect, but teams are using it.
12 months: You're shaping how our data becomes a strategic asset and helping turn it into products that serve our customers.
Location and hours
Remote anywhere in the US. Most collaboration happens on Eastern Time; adjacent time zones are fine with some flexibility. [Travel: e.g., occasional team onsites.]