1 year ago
San Francisco, CA, USAMid Level
Responsibilities
- Build reliable data pipelines and APIs connecting to utilities and public energy sources.
- Architect databases and ingestion systems for time-series energy data, billing, and telemetry.
- Design scalable and cost-efficient GCP infrastructure using services such as BigQuery, Cloud SQL, and Secret Manager.
- Build infrastructure supporting coding agents and AI tools that automate workflows across the stack.
- Set up CI/CD, observability, and automation to support reliable delivery.
- Document work, collaborate across technical and business teams, and communicate impact metrics.
Requirements
- Production experience building data systems with Python, TypeScript, GCP, and SQL or NoSQL.
- Ability to build MVPs quickly and iterate them into robust systems.
- Ability to independently define, scope, and deliver work in a changing startup environment.
- Strong communication skills for explaining technical work to engineers and executives.
- Curiosity about LLMs, agents, and applying AI tools in real systems.
- Ability to select efficient and cost-effective tools using first-principles reasoning.
Benefits
- Hybrid work arrangement in the SF Bay Area with 3 days onsite and 2 days remote.
- Broad ownership and the opportunity to design systems that ship quickly at an early-stage startup.
- Direct collaboration with the co-founder/CTO and exposure to company-wide technical and business impact.
Tech Stack
Categories
Data Engineering
About Pear VC
Pear VC is an early-stage venture capital partnership that invests at pre-seed and seed, pairing capital with hands-on support, mentorship, and programs like its PearX accelerator for founding teams. Founded in 2013 and headquartered in Menlo Park, California, it backs software and technology startups across categories. Its portfolio includes companies that reached the public markets, such as DoorDash and Guardant Health.