Data Engineer | Data & AI

Join a highly skilled Data & AI team delivering a major enterprise transformation programme across a modern Azure data platform. You'll work alongside experienced engineers and architects in a hands-on environment where ownership, technical excellence, and continuous innovation are valued.

Contribute to large-scale data initiatives, modernise enterprise reporting capabilities, and build scalable data solutions using Azure, Databricks, and Python within a collaborative and fast-moving team.

Responsibilities

Build Scalable Data Pipelines: Design, develop, and maintain robust data pipelines that ingest, transform, and deliver enterprise data across multiple business domains.

Develop Data Solutions with Databricks: Leverage Databricks and Python to process large datasets, optimise workflows, and support the delivery of modern data products and reporting solutions.

Support Enterprise Transformation Initiatives: Contribute to large-scale data and reporting transformation programmes, helping ensure data is accurately migrated, transformed, and made accessible for business use.

Partner with Business Stakeholders: Work directly with business users, analysts, and technical teams to understand requirements, challenge assumptions, and translate needs into scalable technical solutions.

Own End-to-End Delivery: Take ownership of data engineering workstreams from requirements gathering and solution design through to development, testing, deployment, and ongoing support.

Improve Data Platform Performance: Monitor and optimise data processing workloads, ensuring high levels of reliability, scalability, and performance across the platform.

Collaborate on Platform Best Practices: Participate in architecture discussions, code reviews, and continuous improvement initiatives to enhance engineering standards and delivery quality.

Contribute to Cloud Data Operations: Support CI/CD, automation, and platform engineering activities within a modern Azure-based data environment.

Enable AI & Advanced Analytics Use Cases: Build and maintain high-quality data foundations that support machine learning, AI initiatives, and advanced analytics across the organisation.

Collaborate with AI Engineering Teams: Work alongside Data Scientists and AI Engineers to prepare, optimise, and operationalise data assets for AI-powered solutions and emerging technologies.

Requirements

5+ years of experience in data engineering.

Strong hands-on experience with Databricks.

Advanced proficiency in Python for data engineering and pipeline development.

Strong SQL skills with experience working with large-scale datasets.

Experience working within the Azure Data ecosystem, including services such as Azure Data Factory and cloud storage solutions.

Experience with Power BI or other BI/reporting tools is advantageous.