Overview Who We Are We are looking for a skilled Data Engineer with strong experience in Databricks and the Azure ecosystem to help build and optimize modern data pipelines for our client, one of the UK’s leading energy providers. The role focuses on developing scalable, high‑performance data processing solutions, implementing robust ETL workflows, and enabling advanced analytics across large‑scale operational and customer datasets. Your expertise will support client’s efforts to modernize its data landscape, enhance real‑time insights, and drive key initiatives in energy distribution, sustainability, and grid innovation within a highly regulated environment.Data Pipeline Development (Batch and Streaming)
Data Modelling & Optimisation
Quality, Governance & Security
Client stakeholders up to Head of Data Engineering, Chief Data Architect, and Analytics leadership
Delivery of high-performing, scalable, and secure data pipelines aligned to client requirements
Improve data engineering practices
Contribution to the growth of the practice through reusable assets, accelerators,



and technical leadership
Minimum 3–8 years in data engineering, data warehousing, or data architecture roles, with at least 3+ years working with Fabric
BSc/MSc in Computer Science, Data Engineering, or related field
Proven experience in data engineering and pipeline development on Fabric, Azure and cloud-native platforms
Strong SQL and Python (or equivalent language) skills for data manipulation and automation
Proficiency in cloud ecosystems (Specifically Azure, optionally AWS and GCP are an advantage) and infrastructure-as-code (e.Knowledge of data modelling methodologies (star schemas, Data Vault, Kimball, Inmon)
Familiarity with medallion architectures, data lakehouse principles and distributed data processing
Experience with version control tools (GitHub, Bitbucket) and CI/CD pipelines
Understanding of data governance, security, and compliance frameworks
Hands-on expertise across the data lifec

📌 Data Engineer (Italia)
🏢 Ntt Data Europe & Latam
📍 Italia