In the next 30 years, the world will transform every part of the built environment to be climate positive green infrastructure. Knowing what, where, and how to build infrastructure like solar farms is one of the great opportunities of our time.
Paces is software for green infrastructure developers to identify the best places to build and manage their projects. Our software supports renewable energy, EV charging, carbon sequestration and data center customers with interconnection, permitting and siting of their projects. We are venture backed from Resolute Ventures & Y Combinator.
🌳 TL;DR
We are looking for a big data expert who is excited about scaling up systems to join us as we grow.
🏆 What You’ll Achieve
- Lead the effort on scale up the existing system to the next level
- Take over infra management and keep our system resilient to spiky traffic
- Build robust ETL solutions to support large scale ML analytics
- Collaborate closely with our CTO and team to directly impact product roadmap
📈 Requirements
- Track record of scaling up systems to the next level as traffic grows
- Familiar with Python, ORMs, databases, and ETL in general
- Comfortable managing data and infra at scale using AWS suite of tools
- You are a proactive and fast learner and able to pick up new things quickly
✨ About You
You will thrive in our culture if you:
- Have a strong bias towards action and prioritize execution
- Share our passion to build something that fights climate change
- Easily handle the unstructured environment of fast moving startups
- Have the hunger to grow together with Paces as we scale up
🚀 Bonus Points
- Previous experience at a high-growth, fast-paced startup
- Previous experience working with geospatial data and platforms
- Previous experience working with ML modeling
- Previous experience scaling up data intensive, AI and analytics heavy solutions
💰 Compensation and Benefits
- 150K - 200K annual compensation
- Competitive equity compensation
- 401(k) matching
- Health, Dental and Vision insurance
- Hybrid working in the office 2-4 times per week