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Salary: USD 170,000 - 260,000 / annual
Vercel is seeking a Senior Data Engineer to own the reliability and accuracy of financial data infrastructure serving Finance stakeholders. The role is full-stack: you'll build and maintain pipelines, transformations, and data models that turn billing and usage data into revenue, forecasting, and reporting systems. Vercel's revenue model combines subscription tiers with usage-based billing across multiple metered products plus Enterprise contracts, making this data genuinely complex.
You'll work closely with Finance teams (FP&A, Accounting, Revenue) to understand how metrics are used and ensure accuracy. Reporting to the Data team's engineering lead, you'll have full ownership over your area, set technical direction, and mentor other engineers.
Key responsibilities include: owning pipelines that bring billing, usage, and contract data into the warehouse reliably; diagnosing and resolving data quality and freshness issues at the source; designing and maintaining dbt models for revenue recognition, margin, and forecasting; setting testing and documentation standards to meet Finance's accuracy requirements; building datasets and semantic models for dashboards and reports; reducing one-off requests through self-service design; partnering with Finance leaders to understand underlying business questions; and mentoring team members.
You'll need 4+ years in data engineering or analytics engineering with a track record of owning production pipelines end-to-end. Strong SQL and Python skills are essential, along with hands-on dbt experience, dimensional/data modeling, and modern ELT/ETL workflows including orchestration tools like Airflow or Dagster. Direct experience with Finance data—ideally usage-based billing, revenue recognition, or financial close/forecasting—is required. You should excel at translating ambiguous business questions into technical specs, communicating trade-offs to both technical and business audiences, and making independent architecture decisions. Comfort with Finance's accuracy and auditability standards (reconciliation, versioning, lineage) is critical.
