Build and improve data pipelines using SQL and Python
Contribute to the development and reliability of our data platform infrastructure
Help design and model datasets that power analytics, internal tools, and AI-driven workflows
Improve data quality, observability, and governance across systems
Support the infrastructure and contextual data layers that enable company-wide agents and interfaces
Partner with engineering, product, finance, and operations stakeholders to translate business needs into scalable data solutions
Depending on your focus, projects may lean more toward:
Data Engineering: modeling, transformation, orchestration, analytics enablement
Data Platform Engineering: infrastructure, tooling, performance optimization, developer experience for data systems

Currently pursuing a BS or MS in Computer Science, Data Science, or a related technical field
Strong proficiency in SQL and Python
Solid understanding of data modeling principles and relational databases
Familiarity with data pipelines, ETL/ELT concepts, or workflow orchestration
Comfort working in a collaborative, fast-moving engineering environment
Strong problem-solving skills and attention to detail
Based in SF/Bay Area & open to commuting to SFHQ 2-3 days a week
Nice to Have:
Experience with modern data stack tools (e.g., dbt, Airflow, Snowflake, BigQuery, etc.)
Exposure to cloud infrastructure (AWS, GCP, or similar)
Experience working with large datasets or analytics systems
Interest in AI/ML systems or agent-based workflows

Real-world experience building production-grade data infrastructure
Exposure to modern data platform architecture at scale
The opportunity to shape systems that power decision-making and AI-driven workflows across Vercel
Mentorship from experienced data and platform engineers
A meaningful, scoped project with measurable impact

Data Platform & Engineering Intern

Key skills