Software Engineer - Data Platform

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 a Staff level Engineer to lead the design and development of a next-generation Data Platform at Vercel. This is a unique opportunity to architect a foundational system that will power data across our products and business, supporting everything from real-time analytics to AI/ML initiatives.

Reporting directly to the Senior Director of Data Engineering, you'll define the technical vision for our data ecosystem, work across the organization to align engineering strategy with product goals, and build scalable, reliable systems using modern technologies like Kafka, ClickHouse, Tinybird, and Snowflake.

You'll lead from the front, writing production-grade code, setting high standards for design and data governance, and mentoring a team of engineers as the organization grows. If you're excited by the challenge of building scalable data systems that drive product innovation, we'd love to hear from you.

What You Will Do

Design and implement a next-generation data platform that supports diverse requirements, including batch and real-time integrations, advanced analytics, and multiple data types, leveraging Kafka, Kafka-based tooling, and additional streaming technologies to power real-time data movement and processing.

Work with engineering, product, and senior leadership teams across Vercel to architect solutions that address business needs, aligning technical strategies with product goals and ensuring seamless data availability and usability.

Define and maintain guidelines for data ingestion, creation, enrichment, and storage, while overseeing data modeling, ETL processes, and data warehousing (ClickHouse, Tinybird, Snowflake) to achieve low-latency analytics and scalable storage.

Develop end-to-end solutions across the tech stack, setting the example for engineering excellence, and provide mentorship and direction that fosters continuous improvement and innovation in the team.

Partner with Security, Compliance, and Legal teams to ensure adherence to data protection standards, and champion high availability and fault tolerance through comprehensive monitoring, alerting, and incident response practices.

Drive architectural decisions and roadmap planning that ensure efficiency, scalability, and high performance, and evaluate build-vs-buy trade-offs, integrating vendor solutions where appropriate.

Collaborate with data scientists and machine learning teams to evolve infrastructure that supports advanced analytics and AI initiatives, serving as a key contributor to strategy, tooling, and platform enhancements for ML-related workloads.

Act as a key decision-maker for discovering, vetting, and selecting data architectures and technologies critical to Vercel's success, and establish multi-phase strategic roadmaps that align with overall business objectives and drive data platform maturity.

About You

8+ years of experience in data engineering, data architecture, or related roles, with at least 5 years at the Principal Engineer level.

Proven track record designing and operating large-scale data infrastructures at high scale 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.

Proficiency in cloud platforms (AWS, GCP, or Azure) and associated big data services.

Strong background in data governance and security, and adept at ensuring compliance with regulatory standards and protecting sensitive information.

Outstanding communication and collaboration skills, with the ability to influence technical and non-technical stakeholders across varying organizational levels.

A leadership mindset, with demonstrated ability to mentor teams, drive consensus, and advocate for best practices across the organization.

A Master's degree in Computer Science, Engineering, or a related field is preferred.