Scaling for MHHS: how Octopus Energy achieved a 50x cost reduction in margin data engineering

Octopus Energy re-architected its data pipeline to handle Half-Hourly Settlement regulations, achieving a 50x cost reduction.

• •Three specialized streams (Settlement, Half-Hourly, Monthly) replaced monolithic monthly processing to match natural data granularity.
• •Delta Lake Change Data Feed reduced rows processed per run from 25B to 300M (98.8% reduction) and improved data freshness from weekly to daily.
• •Spark optimizations including liquid clustering, broadcast joins, and Adaptive Query Execution reduced compute overhead.
• •Databricks Serverless enabled rapid iteration without infrastructure delays, completing the project in three months with three engineers.

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