About the Role:We're looking for a Senior Data Engineer to join our Data team and own the reliability of the data our Finance stakeholders depend on. Vercel's revenue model combines subscription tiers with usage-based billing across many metered products, plus Enterprise contracts, so this data is genuinely complex to get right. This is a full-stack role: you'll build and maintain the pipelines, transformations, and data models that turn billing and usage data into the revenue, forecasting, and reporting infrastructure Finance runs on.
You'll work closely with Finance stakeholders to understand how metrics are used and make sure they're right, not just build to spec. Reporting to the Data team's engineering lead, you'll have full ownership over your area, set technical direction, and help raise the bar for how the team builds financial data infrastructure.
If you want your work to directly shape how the business understands its revenue and financial performance, we'd love to hear from you.
What You Will Do:- Own pipelines that bring billing, usage, and contract data into the warehouse reliably, including metered usage across multiple products.
- Diagnose and resolve data quality and freshness issues at the source, not just downstream.
- Design and maintain dbt models that turn raw billing and usage data into clean, trusted datasets for revenue recognition, margin, and forecasting.
- Set testing and documentation standards so models hold up to the accuracy bar Finance requires when reconciling usage-based revenue against contracts.
- Build datasets and semantic models that power the dashboards and reports Finance leadership uses for planning, forecasting, and close.
- Reduce reliance on one-off requests by designing for self-service.
- Work with Finance leaders (FP&A, Accounting, Revenue) to understand what they need from the data and why, and push back when the ask doesn't match the underlying question.
- Build pipeline and transformation code to a high engineering bar, and hold others to it through code review.
- Mentor other engineers and help set technical standards for the team.
About You:- 4+ years of experience in data engineering, analytics engineering, or a closely related field, with a track record of owning production data pipelines end-to-end
- Strong SQL and Python skills, with experience writing production-grade, testable code, not just scripts for one-off analysis
- Hands-on experience with dbt (or a comparable transformation framework), dimensional/data modeling, and modern ELT/ETL workflows, including orchestration tooling (e.g., Airflow, Dagster)
- Direct experience with Finance data, ideally including usage-based billing, revenue recognition, or financial close/forecasting metrics, with genuine fluency in how those metrics are defined and used
- Proven ability to partner with non-technical stakeholders, translating ambiguous business questions into technical specs and durable data models, not just taking requirements at face value
- Strong communication skills, including presenting technical trade-offs to both technical and business audiences
- A track record of technical ownership, with the judgment to make architecture decisions independently and mentor other engineers
- Comfort with the accuracy and auditability standards Finance data requires (e.g., reconciliation, versioning, clear lineage)
Benefits:- Competitive compensation package, including equity.
- Inclusive Healthcare Package.
- Learn and Grow - we provide mentorship and send you to events that help you build your network and skills.
- Flexible Time Off.
- We will provide you the gear you need to do your role, and a WFH budget for you to outfit your space as needed.
The San Francisco, CA base pay range for this role is $170,000 - $260,000. Actual salary will be based on job-related skills, experience, and location. Compensation outside of San Francisco may be adjusted based on employee location. The total compensation package may include benefits, equity-based compensation, and eligibility for a company bonus or variable pay program depending on the role. Your recruiter can share more details during the hiring process.
