Data Engineer - Azure Databricks & Big Data Pipelines

Rolls-Royce Corporation; East Midlands; On-site; GBP 60,000 - 100,000; Full time

Job summary

Rolls-Royce is recruiting a Data Engineer to join our Derby team, focusing on collecting, parsing, managing, analysing and visualising large data sets. You’ll collaborate with analysts and data scientists, secure the data supply chain and deliver end-to-end data solutions across on‑prem and cloud platforms.

The role requires a degree in Mathematics/Computing or equivalent, 5+ years in Data Engineering with 3 years in a technical lead role, and hands-on experience with Azure Databricks, PySpark,

Qualifications

• Degree-level education in Mathematics or a computing/engineering discipline or equivalent experience.
• 5+ years in Data Engineering with 3+ years in a technical lead role.
• Hands-on with Azure Databricks using PySpark and cluster planning.

Responsibilities

• Understand and implement requirements with colleagues.
• Secure data supply chain and manage data ingestion and transformation.
• Analyse, cleanse, join and transform data to fit solutions.
• Implement designs on the chosen platform and ensure infra meets requirements.
• Plan and test implementations, fix issues and re-test for quality.
• Manage data including security, archiving, structure and storage.

Skills

Technical leadership

Analytical mindset

Problem solving

Education

Degree in Mathematics/Computing

Tools

Azure Databricks

PySpark

SQL Server

Azure Data Factory

Azure DevOps

Spark

Job description

Rolls-Royce is recruiting a Data Engineer to join our Derby team, focusing on collecting, parsing, managing, analysing and visualising large data sets. You’ll collaborate with analysts and data scientists, secure the data supply chain and deliver end-to-end data solutions across on‑prem and cloud platforms.

The role requires a degree in Mathematics/Computing or equivalent, 5+ years in Data Engineering with 3 years in a technical lead role, and hands-on experience with Azure Databricks, PySpark,