Research Engineering Intern – Database Systems (Summer 2027)

Research Engineering Intern – Database Systems (Summer 2027)

Start: May/June 2027

About the Role

We're looking for one engineering intern for Summer 2027, focused on database internals and query execution.

This role is particularly suited to students doing research or advanced coursework in databases, query processing, storage systems, compilers, or related systems areas.

You'll work directly with Hotdata's founders and engineering team on shaping the architecture.

What You'll Work On

• Profile query workloads and identify performance bottlenecks
• Improve query planning, execution, storage, and memory efficiency
• Develop benchmarks to evaluate performance and scalability
• Implement and deploy optimizations in Hotdata
• Contribute improvements upstream to Apache DataFusion, Arrow, Parquet, DuckLake and related projects
• Conduct systems research and publish at leading database conferences (SIGMOD, VLDB, CIDR)

What We're Looking For

• Currently pursuing a PhD in Computer Science or a related field
• Strong background in data infrastructure, distributed systems, query engines, or developer tools
• Experience with at least some of: Rust, Go, Python, Arrow, DataFusion, Postgres, cloud-native infra, serverless architectures
• Deep understanding of performance, concurrency, and scalable system design

Bonus Experience

• Worked on databases, data engines, OLAP systems, or streaming systems
• Experience with vector search, embeddings, or retrieval systems
• Experience contributing to open source systems like Arrow/DataFusion
• Early-stage startup experience building 0→1 systems

Why Join Us

• Shape the core architecture of a breakthrough AI+data infrastructure company
• Work directly with world-class engineers and advisors
• Ownership and autonomy in an early, high-caliber team
• Build technology that will power the next generation of intelligent systems and autonomous agents

How to Apply

Share your resume and any relevant research, publications, benchmarks, open-source contributions, or systems projects you've worked on.

We're particularly interested in students already working on database or systems research who want to apply that experience to a production system.