Castleton Commodities International operates an energy trading and infrastructure asset business built on Python services, cloud analytics (Snowflake, Power BI), and Kubernetes infrastructure. The tech stack reveals an engineering-heavy, infrastructure-first organization mid-migration: they're actively designing cloud-native architectures, automating infrastructure deployment, and transitioning legacy data systems — all while managing complex trading models and fundamental supply-demand forecasting. Hiring acceleration in engineering and senior-level roles signals scaling of both the modernization effort and core product capability.
CCI is an energy markets trader and infrastructure asset investor founded in 2001, headquartered in Stamford, CT. The company combines fundamental research, advanced analytics, and trading operations across energy commodities and physical assets. Their technology platform supports real-time trading processes, pricing models (particularly in power markets), and risk management. The organization is executing a significant cloud and data-stack modernization: moving from legacy systems to Kubernetes-orchestrated services on AWS, adopting Snowflake for analytics, and building cloud-native reporting and visualization tools. Active projects span trading reference data architecture, supply-demand modeling, and disaster recovery infrastructure design.
Core stack includes Python, React/Angular, AWS (EKS, ECS, WAF, Direct Connect), Snowflake, Kubernetes (Helm, Karpenter, Argo CD), Power BI, Terraform, Docker, MATLAB, Datadog, and CI/CD via GitLab and Jenkins.
Active projects include Kubernetes infrastructure modernization, cloud-native analytics and visualization, Python-based trading APIs, supply-demand modeling, power pricing models, and disaster recovery architecture design.
Castleton Commodities International's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.