Senior / Staff Data Engineer

• 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
• 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
• 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 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

Benefits

• Medical, Dental and Vision:
  Comprehensive Aetna, Kaiser, and Guardian coverage for you and your family, with multiple PPO and EPO options available to choose from.
• Mental Health Support: Includes 5 mental health days, Spring Health coaching, and EAP support for you and your family.
• Parental Leave: 16 weeks of fully paid parental leave for all new parents—birthing and non-birthing caregivers—to support time with your growing family.
• Wellness & Safe Leave: 10 paid sick days annually, plus mental health days. We support taking time for your physical and emotional well-being, no justification needed.
• Flexible Time Off: Flexible PTO with a recommended minimum to support rest and recharge. We encourage healthy work-life balance and time away from the screen.
• Remote-Friendly Work: All roles are hybrid (3 days in-office) or fully remote. We prioritize flexibility and async collaboration while staying aligned as a team.
• 401(k) with Accrue: 401(k) plan includes automatic enrollment and flexible contribution options to support your long-term financial planning and retirement goals.
• Team Offsites: We host in-person gatherings to align on goals, strengthen team connections, and build lasting trust beyond day-to-day remote work.
• Commuter Benefits: Use pre-tax funds for public transit and parking expenses—managed through Rippling—to make your daily commute more affordable and efficient.
• Exclusive Discounts: Access to discounts on travel, shopping, entertainment, and more—benefits that extend beyond your workday.

• Typically 6+ years in data engineering, including ownership of platform-level design decisions
• A habit of making your work understandable. You document models, decisions, and strategy so that people outside engineering can use and trust the data
• 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
• 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
• Experience partnering across functions and translating business questions into data requirements, and back again
• Strong Python and SQL
• Experience at a SaaS or software company
• Deep, hands-on production experience with Snowflake and dbt
• Building data that powers customer-facing products, including ML or AI features
• Establishing data governance, SOC 2 controls, or data residency practices
• Fivetran and modern orchestration tools (Airflow, Dagster, or similar)
• Integrating data across clouds or after an acquisition or merger