Data Engineer

You'll be responsible for building and maintaining scalable data pipelines that power analytics and reporting across the organisation. Working within a modern Databricks on AWS environment, you'll help deliver reliable, high-quality data to support business insights., * Build and maintain scalable ETL/ELT pipelines using Python and PySpark

• Ingest and integrate data from multiple sources including trading, finance, and operational systems
• Work within a Databricks Lakehouse architecture to transform and deliver data
• Optimise Spark jobs for performance and cost efficiency
• Implement and maintain data quality, governance, and reliability standards
• Support the full data lifecycle from ingestion through to reporting and insight delivery
• Collaborate with BI teams and stakeholders to ensure data is accessible and usable

• Strong experience in Data Engineering (3-6 years)
• Proficiency in Python and PySpark for large-scale data processing
• Hands-on experience with Databricks (Delta Lake, Workflows, Lakehouse architecture)
• Solid knowledge of AWS services (e.g. S3, Kinesis, Lambda, IAM)
• Experience building production-grade data pipelines
• Good understanding of data governance and data quality frameworks
• Strong SQL skills and experience working with complex datasets

Desirable

• Experience within energy, utilities, or similar complex industries
• Exposure to CI/CD for data pipelines or modern data platform tooling

We're working with a leading organisation operating at the forefront of the energy sector, playing a critical role in supporting the transition to a more sustainable, low-carbon future.