Data Engineer: AI-Ready Lakehouse for Energy Ops

Applied Computing; United Kingdom; Remote; GBP 70,000 - 110,000; Full time

Job summary

Applied Computing in the United Kingdom is seeking a Data Engineer to design and maintain pipelines that convert high-frequency time-series, lab, and historian data into a scalable Lakehouse usable by deep learning models and real-time LLMs.

The role involves working across AWS (EKS, S3, EBS, KMS, CloudWatch) and Databricks/PySpark to contextualise, synchronise, and optimise data for AI workloads while solving cross-domain challenges at the intersection of control systems and industrial data

Qualifications

• Experience architecting and maintaining high-volume data pipelines for AI workloads.
• Strong PostgreSQL tuning, indexing, and data modelling.
• Experience with AWS and Databricks in hybrid cloud environments.

Responsibilities

• Ingest and contextualise data from multiple sources for AI readiness.
• Build real-time and batch pipelines into the Lakehouse and ensure data quality and lineage.
• Optimise data workflows for fast analytics and scalable model training.
• Collaborate across teams to support AI-driven insights and experimentation.

Skills

PostgreSQL

Python

AWS

Databricks

PySpark

Time-series

DCS/SCADA

Streaming

MLOps

Tools

Databricks

Spark

Kubernetes

Flink

Job description

Applied Computing in the United Kingdom is seeking a Data Engineer to design and maintain pipelines that convert high-frequency time-series, lab, and historian data into a scalable Lakehouse usable by deep learning models and real-time LLMs.

The role involves working across AWS (EKS, S3, EBS, KMS, CloudWatch) and Databricks/PySpark to contextualise, synchronise, and optimise data for AI workloads while solving cross-domain challenges at the intersection of control systems and industrial data