Senior Data Engineer – Cloud, SQL Server & Pipelines Lead

Leonardo; West of England; Hybrid; GBP 70,000 - 110,000; Full time

Benefits offered by this job

Hybrid working

Flexible hours

Bonus scheme

Private healthcare

Learning & development

Job summary

Leonardo UK in Bristol is seeking a Senior Data Engineer to design and build secure, scalable data solutions across hybrid environments. You will own data pipelines, collaborate with DevOps, Data Scientists and Analysts, and mentor junior engineers to deliver reliable data platforms.

You’ll work with SQL Server, Python and cloud-native technologies, optimize data architectures, and contribute to security and governance while supporting ML model deployment and operational improvements.

Qualifications

• Proven data engineering experience with ownership of deliverables.
• Strong Python and SQL skills, and building data pipelines.
• Experience with SQL Server and large databases.
• Knowledge of cloud platforms and ETL/orchestration tools.
• Leadership of small work packages and mentoring.

Responsibilities

• Design, administer and optimise SQL Server databases.
• Troubleshoot database issues in development and production.
• Implement and maintain database security, backups and HA.
• Develop tools for data-driven insights and automation.
• Collaborate with DevOps, Data Scientists, Analysts and Cyber Consultants.
• Lead small work packages and provide technical guidance.

Skills

Python

SQL

Data pipelines

Cloud platforms

Mentoring

Education

Bachelor's degree in STEM

Tools

SQL Server

Docker

Kubernetes

Spark

Terraform

Job description

Leonardo UK in Bristol is seeking a Senior Data Engineer to design and build secure, scalable data solutions across hybrid environments. You will own data pipelines, collaborate with DevOps, Data Scientists and Analysts, and mentor junior engineers to deliver reliable data platforms.

You’ll work with SQL Server, Python and cloud-native technologies, optimize data architectures, and contribute to security and governance while supporting ML model deployment and operational improvements.