Energy trading platform for power, gas, and renewables optimization
InCommodities runs a quantitative energy trading operation built on Python, PostgreSQL, Kafka, and F#, with heavy streaming infrastructure (Flink, Kubernetes) and a risk-modeling focus. The tech stack and project list reveal an organization scaling from market data ingestion through real-time trading automation to risk model deployment — a full pipeline from data → decision → execution. Hiring is concentrated in engineering (8 roles) with accelerating velocity, supported by active buildout of Kafka-based streaming, CI/CD, and production risk systems.
InCommodities is a global energy trading firm founded in 2017 in Aarhus, Denmark, now operating across Europe, North America, and Asia Pacific with 250+ employees. The company trades power, gas, and emissions products, with a specialized focus on helping renewable asset owners (solar, wind) optimize output and manage market risk. Their value chain spans market data integration, quantitative analysis, and algorithmic trading — all automated and digitalized. They balance supply and demand across geographies and time horizons, with recent expansion into Japan's power market.
Python, PostgreSQL, Kafka, Apache Flink, F#, Kubernetes, and Azure cloud infrastructure. Supporting tools include pandas, NumPy, SciPy for analytics, and Terraform for infrastructure as code.
Real-time data pipelines (market data integration), Kafka-based streaming ingestion, risk model production deployment, and asset-based trading in Japan's power market. Focus areas include low-latency data systems and scalable Python/F# solutions.
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