Senior Finance Data Engineer: Revenue & Forecasting

vercel.com; San Francisco, Northern (CA, KY); Hybrid; USD 170,000 - 260,000; Full time

Benefits offered by this job

Equity

Healthcare package

Mentorship and events

Flexible time off

WFH budget

Job summary

Vercel in San Francisco, CA is seeking a Senior Data Engineer for the Data team to own the reliability of revenue and usage data used by Finance stakeholders. This full-stack role involves building pipelines, transformations, and data models that turn billing and usage data into revenue recognition, forecasting, and reporting infrastructure.

You'll collaborate with Finance leaders to understand needs, set standards, and mentor others while upholding accuracy and auditability.

Qualifications

• 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)

Responsibilities

• Own pipelines that bring billing, usage, and contract data into the warehouse reliably.
• Diagnose and resolve data quality and freshness issues at the source.
• 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.

Skills

SQL

Python

Production data pipelines

Data modeling

ELT/ETL

Data quality

Stakeholder communication

Mentoring

Tools

dbt

Airflow

Dagster

Job description

Vercel in San Francisco, CA is seeking a Senior Data Engineer for the Data team to own the reliability of revenue and usage data used by Finance stakeholders. This full-stack role involves building pipelines, transformations, and data models that turn billing and usage data into revenue recognition, forecasting, and reporting infrastructure.

You'll collaborate with Finance leaders to understand needs, set standards, and mentor others while upholding accuracy and auditability.