Data Platform Engineer - Finance Vercel Hybrid - San Francisco

About Vercel:

Vercel is the agentic infrastructure company. We free people and agents to ship what’s next.

For more than a decade, Vercel has shaped how the web is built. As the team behind Next.js, v0, and AI SDK, we create products that help builders move from idea to production with speed, security, and exceptional developer experience.

Now, software is entering a new era, and the next generation of products will not just be used by people. They will be built, extended, and operated by agents.

We are building the platform for that future, trusted by companies like OpenAI, Pay Pal, Ramp, Supreme, and millions of developers worldwide
. Whether you’re building our products, supporting our customers, growing our community, or shaping our story, you’ll help define what comes next.

We're looking for a Staff level Engineer to lead the design and development of Vercel's Finance Data Platform, the foundational system that powers revenue reporting, consumption-based billing, financial forecasting, and compliance across the business. This is a unique opportunity to architect the data infrastructure that Finance, Accounting, and Revenue Operations depend on to close the books accurately, forecast revenue with confidence, and scale with the business.

Reporting directly to the Senior Director of Data Engineering, you'll define the technical vision for Vercel's financial data ecosystem, partner closely with Finance, Accounting, and Revenue leadership to translate business and compliance requirements into scalable systems, and build reliable, auditable pipelines using modern technologies like Kafka, Click House, Tinybird, and Snowflake.

You’ll lead from the front, writing production-grade code, setting the bar for data accuracy and governance in a domain where correctness isn't optional, and mentoring a team of engineers as the function grows. If you're excited by the challenge of building financial-grade data systems that the business trusts for reporting, forecasting, and audit, we'd love to hear from you.

• Design and implement a data platform that supports revenue recognition, consumption-based billing, and financial reporting across batch and real-time workloads, leveraging Kafka and streaming technologies to power real-time usage and billing pipelines feeding revenue and consumption forecasts.
• Work directly with FP&A, Accounting, and Rev Ops to understand reporting requirements, close-cycle timelines, and forecasting needs, translating them into technical architecture and ensuring data availability and accuracy align with financial reporting deadlines, audit cycles, and board-level reporting needs.
• Define and maintain guidelines for financial data ingestion, transformation, and storage, with a focus on auditability, lineage, and data integrity, while overseeing data modeling, ETL, and warehousing (Click House, Tinybird, Snowflake) to support low-latency analytics and reliable historical reporting.
• Develop end-to-end solutions across the finance data stack, setting the example for engineering excellence in a high-accountability domain, and mentor engineers on both technical craft and the added rigor required when data feeds directly into financial statements.
• Partner with Security, Compliance, Legal, and Internal Audit to ensure financial data pipelines meet SOX, SOC 2, and other regulatory requirements, and champion high availability, fault tolerance, and auditability through comprehensive monitoring, alerting, and incident response.
• Drive architectural decisions and roadmap planning that balance efficiency, scalability, and the strict correctness requirements of financial systems, and evaluate build-vs-buy tradeoffs across financial and billing tooling (e.g., ERP, billing, and revenue platforms).
• Build the data infrastructure that translates raw usage into revenue, supporting the forecasting models Finance and GTM rely on for target-setting and reporting, and collaborate with data science and FP&A teams on forecasting, incrementality analysis, and revenue modeling at scale.
• Act as a key decision-maker for evaluating and selecting data architectures and technologies critical to Vercel's financial operations, and establish a multi-phase roadmap for finance data platform maturity aligned with company growth and audit readiness.

• Preferred Master's degree in Computer Science, Engineering, or a related field, with 8+ years of experience in data engineering, data architecture, or related roles, including at least 2 years at the Staff/Principal/Lead Engineer level.
• Proven track record designing and operating large-scale data infrastructures in a complex, fast-paced environment, with experience across Kafka and its ecosystem (e.g., Kafka Streams, Confluent Platform), Click House, Tinybird, Snowflake, and broader big data frameworks.
• Prior experience building data pipelines that feed financial reporting, revenue recognition, billing, or consumption-based pricing models, with familiarity with…