Staff Backend Engineer, Compute & Performance (Remote)

Hex Technologies; New York (NY); On-site; USD 221,250 - 348,500; Full time

Benefits offered by this job

Equity

Health benefits

Flexible PTO

Remote work

Job summary

Hex Technologies is seeking a Staff or Principal-level software engineer for its Compute team. The role focuses on computation, performance, data systems design, and systems architecture, driving architectural decisions and shaping the long‑term trajectory of Hex's compute platform while staying hands-on in the codebase.

You will evolve the execution architecture, push parallel execution and caching efforts, instrument systems for performance insights, and collaborate to build capabilities such

Qualifications

• 10+ years of backend engineering experience
• Strong focus on computation, performance, and systems architecture
• Experience with parallel execution strategies and data warehouse computation

Responsibilities

• Evolve Hex's execution architecture to support faster, smarter notebook execution
• Drive parallel execution strategies and caching to reduce latency
• Instrument complex systems to surface performance issues and diagnose time spent
• Collaborate to build platform capabilities, including an internal query language compiling to various warehouses
• Author and review technical proposals; mentor engineers to implement ambitious designs
• Roadmap long‑term designs with milestones across quarters

Skills

Backend engineering

Parallel execution

Caching strategies

System design

Python

TypeScript

Remote collaboration

Tools

Kubernetes

Docker

PostgreSQL

Redis

Terraform

Helm

AWS

Job description

Hex Technologies is seeking a Staff or Principal-level software engineer for its Compute team. The role focuses on computation, performance, data systems design, and systems architecture, driving architectural decisions and shaping the long‑term trajectory of Hex's compute platform while staying hands-on in the codebase.

You will evolve the execution architecture, push parallel execution and caching efforts, instrument systems for performance insights, and collaborate to build capabilities such