Waste-to-energy operator scaling facilities and data infrastructure across UK sites
LondonEnergy converts household waste into electricity and recovers recyclables at scale—their energy plant generates enough power annually for roughly 80,000 homes, while recycling centres maintain a 70% resource recovery rate. The tech stack reflects a hybrid operations business: industrial control systems (Allen-Bradley, Siemens, Rockwell, Valmet PLCs) manage physical assets, while Microsoft Fabric, Python, and SQL support emerging data initiatives. Active hiring is operations-heavy (7 roles) alongside engineering and a nascent data function, with concurrent projects spanning new facility integration, preventative maintenance systems, and cloud data architecture—indicating a shift toward predictive asset management and cross-site operational visibility.
Notable leadership hires: Health & Safety Lead
LondonEnergy operates integrated waste and energy infrastructure across the United Kingdom, established in 1971 and headquartered in London. The business comprises energy-from-waste generation (transforming household and commercial waste into electricity), reuse centres, and recycling operations that process waste streams into recoverable materials. The operational footprint includes multiple facilities requiring coordinated asset management, permitting compliance, and safety oversight. Current strategic work focuses on integrating newly acquired or expanded sites, upgrading mechanical plant reliability, and centralizing data collection across dispersed locations—a transition from site-level siloes to enterprise-wide visibility.
Industrial control (Siemens, Allen-Bradley, Rockwell, Valmet, Mitsubishi), Microsoft ecosystem (Dynamics 365, Azure, Fabric, Office), SQL, Python, Kronos, and CMMS for maintenance. Data and cloud initiatives are active.
New energy recovery facility deployment, integration of acquired assets, waste transfer and recycling facility upgrades, preventative maintenance systems, and cloud-based data platforms and enterprise data models.
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