Energy AI Data Engineer — Real-Time Lakehouse
Summary
A data engineer in London who architects and maintains pipelines converting high-frequency time-series, lab, and historian data into a scalable Lakehouse for deep learning and real-time LLM workloads. Core stack is AWS (EKS, S3, EBS, KMS, CloudWatch) and Databricks, in an energy/industrial AI context.
Applied Computing is seeking a Data Engineer to architect and maintain pipelines turning high-frequency time-series, lab, and historian data into a scalable Lakehouse for deep learning and real-time LLM workloads.
You will work across AWS (EKS, S3, EBS, KMS, CloudWatch) and Databricks, ensuring data is contextualised, synchronised, and optimised for AI workloads while solving problems at the intersection of control systems, industrial data engineering, and AI enablement.