About Carbonfuture
Carbonfuture is the Trust Infrastructure for durable carbon removal. Today, the Trust Infrastructure consists of two products that seamlessly connect the entire carbon removal lifecycle: Carbonfuture MRV+, the most comprehensive MRV solution for durable CDR, and Carbonfuture Marketplace, the leading marketplace for durable CDR. At Carbonfuture, we build trust throughout the carbon removal journey with our rigorous, data-driven approach, ensuring unmatched quality and reliability of carbon removal. We empower suppliers by providing the essential project support and finance needed to transform their carbon removal projects into fully certified carbon credits. For corporate buyers, we offer access to portfolios of carbon removal credits adhering to the highest quality standards and provide visibility at each step of the carbon removal lifecycle via data-driven transparency enabled by Carbonfuture MRV+. We work with some of the world’s most ambitious climate leaders such as Microsoft, Swiss Re, and the World Economic Forum First Movers Coalition.

YOUR ROLE & RESPONSIBILITIES:

As a Data Engineer at Carbonfuture, you will play a key role in shaping our data-driven decision-making and optimizing carbon removal initiatives. Your expertise will contribute to expanding our data capabilities for internal decision-making, supplier support, and market insights.

WHAT YOU’LL DO:

• Build tools and dashboards that provide actionable insights for internal teams, suppliers, and buyers to optimize carbon removal efforts and business decisions.
• Expand and maintain our data warehouse by integrating internal and external data sources, including HubSpot, our MRV+ product, third-party registries, and marketplaces.
• Ensure data accuracy, integrity, and health by implementing necessary transformations and monitoring data quality.
• Optimize product reporting and database performance to improve efficiency and scalability.
• Develop a roadmap for expanding our data infrastructure, including support for large-scale, machine-learning-assisted analytics.
• Train and support internal users in leveraging data visualization tools effectively.