Asks for

The ad says“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.”
The ad says“Proficiency in cloud platforms (AWS, GCP, or Azure) and associated big data services.”
The ad says“Proficiency in cloud platforms (AWS, GCP, or Azure) and associated big data services.”
The ad says“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), ClickHouse, Tinybird, Snowflake, and broader big data frameworks.”
The ad says“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), ClickHouse, Tinybird, Snowflake, and broader big data frameworks.”
The ad says“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.”
The ad says“Strong background in data governance, security, and compliance, including direct experience supporting audit, SOX, or SOC 2 requirements, and a rigorous approach to data lineage and accuracy.”
The ad says“Proficiency in cloud platforms (AWS, GCP, or Azure) and associated big data services.”
The ad says“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), ClickHouse, Tinybird, Snowflake, and broader big data frameworks.”
The ad says“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), ClickHouse, Tinybird, Snowflake, and broader big data frameworks.”
The ad says“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), ClickHouse, Tinybird, Snowflake, and broader big data frameworks.”
The ad says“Strong background in data governance, security, and compliance, including direct experience supporting audit, SOX, or SOC 2 requirements, and a rigorous approach to data lineage and accuracy.”
The ad says“Strong background in data governance, security, and compliance, including direct experience supporting audit, SOX, or SOC 2 requirements, and a rigorous approach to data lineage and accuracy.”
The ad says“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), ClickHouse, Tinybird, Snowflake, and broader big data frameworks.”

About Vercel:

Vercel is the agentic infrastructure company, freeing people and agents to ship what's next. For more than a decade we've helped builders move from idea to production with speed, security, and exceptional developer experience.

Now we're scaling our products for both agents and people to ship and run software, built in the open and trusted by OpenAI, PayPal, Ramp, Supreme, and millions of developers worldwide.

About the Role

We're looking for an 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, ClickHouse, 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.

What You Will Do

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 RevOps 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 (ClickHouse, 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.

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.
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), ClickHouse, 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 financial/ERP systems (e.g., NetSuite, Workday) or billing platforms considered a strong plus.
Proficiency in cloud platforms (AWS, GCP, or Azure) and associated big data services.
Strong background in data governance, security, and compliance, including direct experience supporting audit, SOX, or SOC 2 requirements, and a rigorous approach to data lineage and accuracy.
Outstanding communication and collaboration skills, with the ability to translate financial and accounting requirements into technical architecture and influence both technical and non-technical stakeholders, including Finance and Audit leadership.
A leadership mindset, with demonstrated ability to mentor teams, drive consensus, and advocate for best practices in high-accountability data environments.
Industry recognition or notable contributions in data engineering (e.g., published works, open-source contributions) is a plus.

Compensation & 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 $190,000 - $258,000. 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.

Disclosures:

Privacy: Please review our Job Applicant Privacy Policy for more information on how we handle your data.
Equal Opportunity: Vercel is committed to fostering and empowering an inclusive community within our organization. We do not discriminate on the basis of race, religion, color, gender expression or identity, sexual orientation, national origin, citizenship, age, marital status, veteran status, disability status, or any other characteristic protected by law. Vercel encourages everyone to apply for our available positions, even if they don't necessarily check every box on the job description.