Overcoming Challenges in Clean Energy Project Development

Published On Wed May 21 2025
Overcoming Challenges in Clean Energy Project Development

Data Engineer @ Paces (YC S22) | Tech:NYC Job Board

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. However, there are problems!

The Problem

80% of clean energy projects developers start never actually get built because most projects are started without deep due diligence on zoning and interconnection due to the cost of collecting that data. This means $17B worth of canceled projects per year.

Our Solution

Paces is software for green infrastructure developers to identify the best places to build and manage their projects. First, we collect environmental, permitting, zoning, energy grid data from various different sources; then we analyze the data and use AI to identify the best places for developers to build their next projects.

Our Team

We are building a team where people can proudly say their time at Paces was the most impactful, meaningful work of their career. Our amazing team in Brooklyn, New York includes incredible engineers and growth team members from companies like AWS, Meta AI, Deepmind, Replica, Yotpo, Rent The Runway & Leap. Paces is growing rapidly and looking for exceptional people to join who want to have a massive positive climate impact while building a great culture! We are looking for a data engineer passionate about building robust data pipelines as we scale up.

🏆 What You’ll Achieve

Design, implement, and maintain scalable ETL data pipelines from hundreds of data sources. Optimize our storage and retrieval systems for performance and reliability. Ensure data quality, consistency, and security across the platform. Collaborate closely with our CTO, Data Infra Lead, Product Lead, and team to directly impact the product roadmap.

Optimizing data pipeline with Big Data analytics

Requirements

Solid understanding of data engineering concepts, with a strong grasp of data structures, algorithms, and system design. Strong coding skills with demonstrated proficiency in relevant programming languages, such as Python, Rust, Scala. Advanced SQL expertise, including experience with complex queries, query optimization, and working with various database systems. Hands-on experience with big data tools (e.g. Spark) and data pipeline orchestration tools (e.g. Dagster, Airflow, Prefect). Proven experience in building robust, scalable, and performant data pipelines on the cloud (AWS / GCP / Azure).

✨ About You

You will thrive in our culture if you: Have a strong bias towards action and prioritize results over processes. 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 (geo)spatial datasets and libraries (e.g. GEOS, GDAL). Hands-on experience with novel data tools and frameworks such Apache Arrow, DuckDB, DeltaLake, Apache Iceberg.

How To Improve Data Pipeline Optimization

Compensation and Benefits

120K - 170K annual compensation. Competitive equity compensation. 401(k) matching. Health, Dental, and Vision insurance. Hybrid working in the office 2-4 times per week.