Building a Cloud-Native Data Platform for Energy Trading Analytics
The Client
A leading global commodities trading group active across energy, metals, and bulk commodity markets. The organisation operates large-scale international trading activities spanning physical supply chains and derivatives markets, managing complex commercial operations across multiple geographies.
Within its energy division, the firm runs sophisticated power trading operations supported by quantitative analytics, market intelligence, and structured risk management capabilities. Its trading desks integrate market pricing, asset data, and fundamental datasets to support decision-making in highly dynamic commodity markets.
The Challenge
The energy trading division relied on multiple external market data providers delivering pricing, asset, and fundamental datasets with different structures, update frequencies, and integration mechanisms. Data ingestion processes were fragmented and not industrialised, limiting scalability and increasing operational dependency on manual handling and ad-hoc workflows.
The trading and analytics teams required timely access to reliable, standardised datasets to support quantitative modelling, pricing analysis, and risk assessment. However, inconsistencies in data formats, varying ingestion patterns (batch, event-driven), and the absence of a unified lifecycle model made it difficult to efficiently prepare and expose data for analytics consumption.
The organisation needed to design and implement a scalable cloud-native Data Platform MVP capable of industrialising ingestion, standardisation, storage, and governed data access—while remaining modular, extensible, and aligned with future enterprise architecture evolution.
Our Solution
The Value
